CN111324740A - Dispute event identification method, dispute event identification device and dispute event identification system - Google Patents
Dispute event identification method, dispute event identification device and dispute event identification system Download PDFInfo
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Abstract
The application discloses a dispute event identification method, device and system. Wherein, the method comprises the following steps: acquiring dispute description information of dispute events; determining a search result of a dispute event based on dispute description information and a pre-constructed dispute knowledge graph, wherein the dispute knowledge graph at least comprises entity elements in historical dispute description information and a logical relationship between the entity elements in the historical dispute description information; and sending the search result to the user end device. The dispute event identification method and the dispute event identification system solve the technical problem that an existing dispute adjustment system is inaccurate in dispute event identification.
Description
Technical Field
The application relates to the field of computers, in particular to a dispute event identification method, device and system.
Background
With the rapid development of computer technology, the internet brings convenience to all aspects of people's life and work. In life, people can purchase commodities without going out of home; in work, people can realize remote office. People can also mediate disputes through the Internet. However, there are a plurality of entries in the existing conflict mediation system, and when people report dispute events through the conflict mediation system, the same event may be reported through different entries for a plurality of times, and for the same conflict event, for example, a party may report to the conflict mediation system independently; alternatively, for the same contradictory event, the same party may report to the contradiction mediation system repeatedly for many times. Therefore, in the dispute event mediation process, multiple departments mediate the same event at the same time, different mediation results may be obtained, and the "mistaken injuries" between different departments may be caused, so that the dispute event identification is inaccurate.
In view of the above problems, no effective solution has been proposed.
Disclosure of Invention
The embodiment of the application provides a dispute event identification method, a dispute event identification device and a dispute event identification system, and at least solves the technical problem that an existing contradiction mediation system is inaccurate in dispute event identification.
According to an aspect of an embodiment of the present application, a method for identifying a dispute event is provided, including: acquiring dispute description information of dispute events; determining a search result of a dispute event based on dispute description information and a pre-constructed dispute knowledge graph, wherein the dispute knowledge graph at least comprises entity elements in historical dispute description information and a logical relationship between the entity elements in the historical dispute description information; and sending the search result to the user end device.
According to another aspect of the embodiments of the present application, there is also provided an apparatus for identifying a dispute event, including: the dispute management system comprises an acquisition module, a dispute management module and a dispute management module, wherein the acquisition module is used for acquiring dispute description information of dispute events; the dispute management module is used for determining a search result of a dispute event based on dispute description information and a pre-constructed dispute knowledge graph, wherein the dispute knowledge graph at least comprises entity elements in historical dispute description information and a logical relationship between the entity elements in the historical dispute description information; and the sending module is used for sending the search result to the target object.
According to another aspect of the embodiments of the present application, there is also provided a system for identifying a dispute event, including: a communication module and a processor; the communication module is used for receiving a query request of a user and sending a search result of the processor to the user end equipment; the processor is used for acquiring dispute description information of dispute events and a pre-constructed dispute knowledge graph under the triggering of the query request, wherein the dispute knowledge graph at least comprises entity elements in the historical dispute description information and a logical relationship between the entity elements in the historical dispute description information; and determining a search result of the dispute event based on the dispute description information and a pre-constructed dispute knowledge graph.
According to another aspect of the embodiments of the present application, there is also provided a storage medium including a stored program, wherein when the program runs, the apparatus on which the storage medium is controlled performs the following steps: acquiring dispute description information of dispute events and a pre-constructed dispute knowledge graph; determining a search result of a dispute event based on dispute description information and a pre-constructed dispute knowledge graph, wherein the dispute knowledge graph at least comprises entity elements in historical dispute description information and a logical relationship between the entity elements in the historical dispute description information; and sending the search result to the user end device.
In the embodiment of the application, a mode of identifying dispute events based on a knowledge graph is adopted, after dispute description information of the dispute events is obtained, a search result of the dispute events is determined based on the dispute description information and a pre-constructed dispute knowledge graph, and the search result is sent to user equipment, wherein the dispute knowledge graph at least comprises entity elements in historical dispute description information and a logical relationship between the entity elements in the historical dispute description information.
In the process, because the dispute knowledge graph comprises the entity elements and the logical relationship between the entity elements, dispute events reported by the same event through different inlets can be automatically identified in a mode based on the dispute knowledge graph, the same department is guaranteed to process the same dispute event, interference of irrelevant information is avoided, and the accuracy of the search result of the dispute event is improved.
Therefore, the technical problem that the dispute event identification is inaccurate by the existing contradiction mediation system can be solved by the scheme provided by the application.
Drawings
The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the application and together with the description serve to explain the application and not to limit the application. In the drawings:
fig. 1 is a block diagram of a hardware structure of a computer terminal for implementing a dispute event identification method according to an embodiment of the present application;
FIG. 2 is a flowchart of a dispute event identification method according to an embodiment of the present disclosure;
fig. 3 is a schematic diagram of a display interface of an alternative client device according to an embodiment of the present application;
FIG. 4 is a schematic diagram of an alternative dispute knowledge-graph structure according to an embodiment of the present application;
FIG. 5 is an architecture diagram of an alternative dispute event based identification method according to an embodiment of the present application;
fig. 6 is a schematic structural diagram of a dispute event recognition apparatus according to an embodiment of the present application;
FIG. 7 is a block diagram of a computer terminal according to an embodiment of the present application;
fig. 8 is a flowchart of a dispute event identification method according to an embodiment of the present application. And
Detailed Description
In order to make the technical solutions better understood by those skilled in the art, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only partial embodiments of the present application, but not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
It should be noted that the terms "first," "second," and the like in the description and claims of this application and in the drawings described above are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used is interchangeable under appropriate circumstances such that the embodiments of the application described herein are capable of operation in sequences other than those illustrated or described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
First, some terms or terms appearing in the description of the embodiments of the present application are applicable to the following explanations:
and the entity relationship extraction refers to extracting and marking entities from natural texts and relationships among the entities.
Knowledge Graph, also known as scientific Knowledge Graph, refers to a semantic network obtained by aggregating entities and relationships between the entities
The graph path mode refers to a connection mode of nodes and edges in graph theory.
Example 1
There is also provided, in accordance with an embodiment of the present application, an embodiment of a method for dispute event identification, where it is noted that the steps illustrated in the flowchart of the drawings may be performed in a computer system such as a set of computer-executable instructions, and that while a logical order is illustrated in the flowchart, in some cases the steps illustrated or described may be performed in an order different than here.
The method provided by the first embodiment of the present application may be executed in a mobile terminal, a computer terminal, or a similar computing device. Fig. 1 shows a hardware configuration block diagram of a computer terminal (or mobile device) for implementing a dispute event identification method. As shown in fig. 1, the computer terminal 10 (or mobile device 10) may include one or more (shown as 102a, 102b, … …, 102 n) processors 102 (the processors 102 may include, but are not limited to, a processing device such as a microprocessor MCU or a programmable logic device FPGA, etc.), a memory 104 for storing data, and a transmission device 106 for communication functions. Besides, the method can also comprise the following steps: a display, an input/output interface (I/O interface), a Universal Serial Bus (USB) port (which may be included as one of the ports of the I/O interface), a network interface, a power source, and/or a camera. It will be understood by those skilled in the art that the structure shown in fig. 1 is only an illustration and is not intended to limit the structure of the electronic device. For example, the computer terminal 10 may also include more or fewer components than shown in FIG. 1, or have a different configuration than shown in FIG. 1.
It should be noted that the one or more processors 102 and/or other data processing circuitry described above may be referred to generally herein as "data processing circuitry". The data processing circuitry may be embodied in whole or in part in software, hardware, firmware, or any combination thereof. Further, the data processing circuit may be a single stand-alone processing module, or incorporated in whole or in part into any of the other elements in the computer terminal 10 (or mobile device). As referred to in the embodiments of the application, the data processing circuit acts as a processor control (e.g. selection of a variable resistance termination path connected to the interface).
The memory 104 may be used to store software programs and modules of application software, such as program instructions/data storage devices corresponding to the method for identifying a dispute event in the embodiment of the present application, and the processor 102 executes various functional applications and data processing by running the software programs and modules stored in the memory 104, so as to implement the method for identifying a dispute event. The memory 104 may include high speed random access memory, and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some examples, the memory 104 may further include memory located remotely from the processor 102, which may be connected to the computer terminal 10 via a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
The transmission device 106 is used for receiving or transmitting data via a network. Specific examples of the network described above may include a wireless network provided by a communication provider of the computer terminal 10. In one example, the transmission device 106 includes a Network adapter (NIC) that can be connected to other Network devices through a base station to communicate with the internet. In one example, the transmission device 106 can be a Radio Frequency (RF) module, which is used to communicate with the internet in a wireless manner.
The display may be, for example, a touch screen type Liquid Crystal Display (LCD) that may enable a user to interact with a user interface of the computer terminal 10 (or mobile device).
It should be noted here that, in some embodiments, the computer device (or mobile device) shown in fig. 1 has a touch display (also referred to as a "touch screen" or "touch display screen"). In some embodiments, the computer device (or mobile device) shown in fig. 1 above has a Graphical User Interface (GUI) with which a user can interact by touching finger contacts and/or gestures on a touch-sensitive surface, where the human interaction functionality optionally includes the following interactions: executable instructions for creating web pages, drawing, word processing, making electronic documents, games, video conferencing, instant messaging, emailing, call interfacing, playing digital video, playing digital music, and/or web browsing, etc., for performing the above-described human-computer interaction functions, are configured/stored in one or more processor-executable computer program products or readable storage media.
Under the operating environment, the application provides a dispute event identification method as shown in fig. 2. Fig. 2 is a flowchart of a dispute event identification method according to a first embodiment of the present application, and as can be seen from fig. 2, the method includes the following steps:
step S202, dispute description information of dispute events is obtained.
It should be noted that the server may be used as an execution main body of the dispute event identification method provided by the present application, where the server communicates with the user end device, the user inputs dispute description information of the dispute event to the server through the user end device, and the server may obtain the dispute description information of the dispute event through the user end device.
Optionally, the dispute event in step S202 may include, but is not limited to, a civil dispute (e.g., a property dispute), an administrative dispute (e.g., a medical and health dispute), a legal complaint dispute, and the like. The dispute event description information includes description information of a plurality of dispute events, and the description information of the dispute events includes, but is not limited to, time, place, case-involved persons, and content of the dispute events.
In addition, it should be further noted that the user may input the description information of the dispute event through the user end device, where the user end device may have a plurality of entries, and the user may input the description information of the dispute event through the entries, for example, as shown in a display interface of the user end device shown in fig. 3, the user may input the description information of the dispute event by clicking a "village dispute" control to enter the corresponding interface, or may input the description information of the dispute event by clicking a "noise harassment" control to enter the corresponding interface. Optionally, after the dispute description information of the dispute event is acquired, the server may further store the dispute description information of the dispute event input by the user, where the dispute description information is stored in the data server, or may be stored in a database of the device in which the server is located, and a specific storage location is not limited in the present application.
And S204, determining a search result of the dispute event based on the dispute description information and a pre-constructed dispute knowledge graph, wherein the dispute knowledge graph at least comprises entity elements in the historical dispute description information and a logical relationship between the entity elements in the historical dispute description information.
It should be noted that the dispute knowledge graph constructed in advance may be stored in the server, and after the dispute description information is obtained, the server uses the dispute description information input by the user as an input of the dispute knowledge graph to obtain a search result of the dispute knowledge graph.
Optionally, fig. 4 shows a schematic structural diagram of an optional dispute knowledge graph, where each node in fig. 4 represents an entity element in the dispute knowledge graph, and a connection line between the nodes represents a logical relationship between the entity elements, for example, node a1 and node a2 obtain node A3 after logical processing, node A3 obtain node a4 after logical processing, node B1, node B2, node B3, and node B4 obtain node B5 after logical processing, node B5 obtain node B6 after logical processing, and node a4 and node B6 obtain a search result S after logical processing. In the above process, the logical relationship between the entity elements includes, but is not limited to, delinquent wages, village disputes, enterprise principals, and the like. For example, if node a1 and node a2 in fig. 4 are debtors, node A3 is a borrower, and the borrower borrows money from the debtors, the logical relationship between node A3 and nodes a1 and a2 is debt. For another example, if node A3 is the building material manufacturer, node a4 is the construction company, and the construction company owes the construction manufacturer, the logical relationship between node A3 and node a4 is owed.
In an alternative scheme, different types of dispute events correspond to different dispute knowledge graphs. After obtaining the dispute description information input by the user, the server determines the dispute type of the dispute event according to the dispute description information, for example, the server extracts a keyword from the dispute description information, and after obtaining the keyword, the server determines the dispute type of the dispute event according to the keyword and the semantics of the context of the keyword, wherein the dispute type of the dispute event includes, but is not limited to, civil dispute, administrative dispute, legal dispute and the like. After the dispute type of the dispute event is determined, the server determines a dispute knowledge graph corresponding to the dispute type according to the dispute type of the dispute event, and further obtains a search result of the dispute event according to the dispute description information and the corresponding dispute knowledge graph.
Step S206, sending the search result to the user end device.
It should be noted that, in step S206, the search result of the dispute event may include whether multiple dispute events are the same event, and/or which dispute events are the same event.
It should be noted that the user end device may be a terminal device used by a user who inputs historical dispute description information of a dispute event, or may be a terminal device used by a user who handles the dispute event (for example, a staff member who regulates the dispute event).
In an optional scheme, after the search result of the dispute event is obtained, the server sends the relevant information of the dispute event to the terminal device of the staff handling the dispute event according to the search result, so that the staff can handle the dispute event. Meanwhile, the server can also send the search result to the terminal equipment used by the party who generates the dispute so that the party can know the relevant information of the dispute event, such as the department handling the dispute event, the property of the dispute event, and the like.
Based on the schemes defined in the above steps S202 to S206, it can be known that, after obtaining historical dispute description information of a dispute event by using a mode of identifying the dispute event based on a knowledge graph, determining a search result of the dispute event based on the dispute description information and a pre-constructed dispute knowledge graph, and sending the search result to the user end device, where the dispute knowledge graph at least includes entity elements in the historical dispute description information and a logical relationship between the entity elements in the historical dispute description information.
It is easy to note that, because the dispute knowledge graph includes the entity elements in the historical dispute description information and the logical relationship between the entity elements, the dispute events reported by the same event through different entries can be automatically identified in a mode based on the dispute knowledge graph, so that the same department can be guaranteed to process the same dispute event, interference of irrelevant information is avoided, and the accuracy of the search result of the dispute event is improved.
Therefore, the technical problem that the dispute event identification is inaccurate by the existing contradiction mediation system can be solved by the scheme provided by the application.
In some embodiments of the present application, the dispute description information may be structured information, where the structured information at least includes entity elements of the dispute description information and logical relationships between entities, and the dispute knowledge graph is equivalent to the historical event library and at least includes structured information of all historical events.
In an alternative scheme, before determining the search result of the dispute event based on the dispute description information and the pre-constructed dispute knowledge graph, the server needs to determine the dispute knowledge graph. Specifically, the server firstly extracts word features and character features from historical dispute description information, then inputs the word features and the character features into a preset learning model for recognition, obtains entity elements of dispute events and logical relations among the entity elements, and finally constructs a dispute knowledge graph based on the entity elements and the logical relations.
It should be noted that the dispute description information of the dispute event may be dispute description information input by the user, or may be dispute description information read by the server from a case set of historical dispute events. Optionally, the case set of historical dispute events is stored in a data server.
Optionally, as shown in the architecture diagram of the dispute event-based identification method shown in fig. 5, the preset learning model may be, but is not limited to, a Bi-directional Long Short-Term Memory (Bi-directional recurrent neural network) model, where Word features and character features input to the Bi-LSTM model are Word embedding and Char embedding. After Word embedding and Char embedding are input into the Bi-LSTM model, the server processes the output result of the Bi-LSTM model by using a CRF (Conditional Random Field Algorithm) Algorithm to obtain entity elements of a dispute event and a logical relationship between the entity elements, and obtains three entities (i.e., entity 1, entity 2, and entity 3) and three logical relationships (i.e., relationship 1, relationship 2, and relationship 3) as shown in fig. 5. After the entity elements of the dispute event and the logical relationship between the entity elements are obtained, the server constructs a dispute knowledge graph based on the entity elements and the logical relationship, namely the dispute knowledge graph is obtained through mode matching.
In an optional scheme, after a dispute knowledge graph is determined and dispute description information of a dispute event is obtained, a server extracts a logical relationship between at least one entity element and at least one entity element from the dispute description information, determines a node corresponding to the at least one entity element in the dispute knowledge graph based on the logical relationship between the at least one entity element and the at least one entity element, searches based on a common neighbor algorithm, determines neighbor nodes of the node, determines a candidate event set based on the node corresponding to the at least one entity element and the neighbor nodes, and finally determines a target event from the candidate event set and takes the target event as a search result of the dispute event.
In the above process, the entity elements at least include the time, the place, the involved persons, the event content, and the like of the dispute event, and the logical relationship between the entity elements may include, but is not limited to, delinquent wages, village disputes, business managers, and the like. For example, if node a is zhang three, node B is lie four, and zhang three is the enterprise principal of lie four, then the enterprise principal is the logical relationship between node a and node B. For another example, if node C is company XX, node D is farmer, and company XX owes the salary of the farmer, then the logical relationship between node C and node D is the owed salary.
In an optional scheme, as can be seen from fig. 5, before determining a node corresponding to at least one entity element in the dispute knowledge graph based on the logical relationship between the at least one entity element and the at least one entity element, the server further performs normalization processing on the logical relationship between the at least one entity element and the at least one entity element to obtain normalized data, and inputs the normalized data into the dispute knowledge graph. The server matches at least one entity element and logic relationship with data in a preset standard data set, and takes the matched data as standardized data.
It should be noted that different types of entity elements have different standardization processes, for example, for address entity elements, an address engine may be used to standardize them; the organization entity can be standardized by spelling error correction.
In addition, after the entity elements and the logical relationship between the entity elements are standardized to obtain standardized data, the server updates the dispute knowledge graph based on the obtained standardized data.
Optionally, after the dispute knowledge graph is updated, the server determines a node corresponding to the entity element in the updated dispute knowledge graph, and combines the node with a neighbor node obtained through a common neighbor algorithm to obtain a candidate event set, for example, if the neighbor node of the node a is the node B, the dispute event composed of the node a and the node B is taken as a candidate event; and if the neighbor node of the node C is the node D, taking a dispute event formed by the node C and the node D as another candidate event. Wherein the plurality of candidate events constitute a set of candidate events.
Further, the server ranks the candidate events in the candidate event set according to the event type of each candidate event in the candidate event set and the node type corresponding to the at least one entity element, and determines the target event based on a preset number of candidate events with the highest rank. Specifically, the server determines a first scoring index and a first weight of an event type and a second scoring index and a second weight corresponding to the node type for each candidate event, then determines a final scoring index of each candidate event based on the first scoring index, the first weight, the second scoring index and the second weight, and finally ranks the candidate events in the candidate event set based on the final scoring index.
It should be noted that, in the foregoing process, each node in the dispute knowledge graph has a node characteristic, where the node characteristic includes an event type and a node type of the node, where the event type represents the type of the dispute event, for example, a village dispute and a noise citizen dispute; the node type represents the specific content of the node, such as a mobile phone number, a business name, an organization name, a time and date and the like. Optionally, the second weight corresponding to the node type with higher accuracy is larger, for example, the weight of the mobile phone number is higher than that of the organization name.
In an alternative scheme, after obtaining a final score indicator of each candidate event according to the event type and the node type of each candidate event, the server ranks the candidate events according to the final score indicator of each candidate event, and determines target events based on a preset number of candidate events with the highest rank, for example, the top 10% of the candidate events in the rank are selected as the target events.
Further, as shown in fig. 5, after the dispute knowledge graph is generated, the server also feeds back the search result obtained based on the dispute knowledge graph to the user end device, so that the user can check the search result, and process the dispute event according to the search result.
It should be noted that by the scheme provided by the application, the dispute event is identified through the dispute knowledge graph, so that interference of stop words and key information of the non-dispute event is avoided, and the accuracy of dispute event identification is improved. In addition, the key entity information of the dispute scene is subjected to standardized processing, and the recall rate of the dispute event identification is improved.
It should be noted that, for simplicity of description, the above-mentioned method embodiments are described as a series of acts or combination of acts, but those skilled in the art will recognize that the present application is not limited by the order of acts described, as some steps may occur in other orders or concurrently depending on the application. Further, those skilled in the art should also appreciate that the embodiments described in the specification are preferred embodiments and that the acts and modules referred to are not necessarily required in this application.
Through the above description of the embodiments, those skilled in the art can clearly understand that the method for identifying a dispute event according to the above embodiments can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware, but the former is a better implementation manner in many cases. Based on such understanding, the technical solutions of the present application may be embodied in the form of a software product, which is stored in a storage medium (e.g., ROM/RAM, magnetic disk, optical disk) and includes instructions for enabling a terminal device (e.g., a mobile phone, a computer, a server, or a network device) to execute the method according to the embodiments of the present application.
Example 2
According to an embodiment of the present application, there is also provided a dispute event recognition apparatus for implementing the dispute event recognition method, as shown in fig. 6, the apparatus 60 includes: an acquisition module 601, a determination module 603, and a sending module 605.
The obtaining module 601 is configured to obtain historical dispute description information of a dispute event; the determining module 603 is configured to determine a search result of the dispute event based on the historical dispute description information and a pre-constructed dispute knowledge graph, where the dispute knowledge graph at least includes entity elements in the historical dispute description information and a logical relationship between the entity elements in the historical dispute description information; a sending module 605, configured to send the search result to the target object.
It should be noted here that the acquiring module 601, the determining module 603, and the sending module 605 correspond to steps S202 to S206 in embodiment 1, and the three modules are the same as the corresponding steps in the implementation example and application scenario, but are not limited to the disclosure in the first embodiment. It should be noted that the modules described above as part of the apparatus may be run in the computer terminal 10 provided in the first embodiment.
In an alternative, the determining module includes: the device comprises an extraction module, a first determination module, a second determination module, a third determination module and an identification module. The extracting module is used for extracting at least one entity element and a logical relationship between the at least one entity element from the dispute description information; the first determination module is used for determining a node corresponding to at least one entity element in the dispute knowledge graph based on the at least one entity element and the logic relationship between the at least one entity element; the second determining module is used for searching based on a common neighbor algorithm and determining neighbor nodes of the nodes; a third determining module, configured to determine a candidate event set based on a node and a neighboring node corresponding to at least one entity element; and the identification module is used for determining the target event from the candidate event set and taking the target event as a search result of the dispute event.
In an optional scheme, the device for identifying a dispute event further includes: a processing module and an input module. The processing module is used for standardizing at least one entity element and the logic relation between the at least one entity element to obtain standardized data; and the input module is used for inputting the standardized data to the dispute knowledge graph.
In an alternative, the processing module comprises: and a matching module. The matching module is used for matching at least one entity element and logic relation with data in a preset standard data set, and taking the matched data as standardized data.
Optionally, the dispute events are multiple, and the historical dispute description information includes description information of the dispute events.
In an alternative, the identification module comprises: a first ordering module and a fourth determining module. The first ordering module is used for ordering the candidate events in the candidate event set according to the event type of each candidate event in the candidate event set and the node type corresponding to at least one entity element; and the fourth determining module is used for determining the target event based on the candidate events with the highest ranking and preset number.
In an alternative, the first sequencing module includes: the device comprises a fifth determining module, a sixth determining module and a second sorting module. The fifth determining module is used for determining a first scoring index and a first weight of an event type and a second scoring index and a second weight corresponding to a node type for each candidate event; a sixth determining module, configured to determine a final scoring index for each candidate event based on the first scoring index, the first weight, the second scoring index, and the second weight; and the second sorting module is used for sorting the candidate events in the candidate event set based on the final scoring index.
In an alternative, the dispute knowledge-graph is determined by: extracting word features and character features from historical dispute description information; inputting the word features and the character features into a preset learning model for recognition to obtain entity elements of dispute events and logic relations among the entity elements; and constructing a dispute knowledge graph based on the entity elements and the logical relationship.
Example 3
According to an embodiment of the present application, there is also provided a dispute event recognition system for implementing the dispute event recognition method, where the dispute event recognition system includes: a communication module and a processor; wherein,
the communication module is used for receiving a query request of a user and sending a search result of the processor to the user end equipment; the processor is used for acquiring dispute description information of dispute events and a pre-constructed dispute knowledge graph under the triggering of the query request, wherein the dispute knowledge graph at least comprises entity elements in the historical dispute description information and a logical relationship between the entity elements in the historical dispute description information; and determining a search result of the dispute event based on the dispute description information and a pre-constructed dispute knowledge graph.
As can be seen from the above, after dispute description information of a dispute event is obtained by adopting a mode of identifying the dispute event based on a knowledge graph, a search result of the dispute event is determined based on the dispute description information and a pre-established dispute knowledge graph, and the search result is sent to the user end device, where the dispute knowledge graph at least includes entity elements in the historical dispute description information and a logical relationship between the entity elements in the historical dispute description information.
It is easy to note that, because the dispute knowledge graph includes the entity elements and the logical relationship between the entity elements, dispute events reported by different entries for the same event can be automatically identified by a mode based on the dispute knowledge graph, so that the same department can be guaranteed to process the same dispute event, interference of irrelevant information is avoided, and the accuracy of the search result of the dispute event is improved.
Therefore, the technical problem that the dispute event identification is inaccurate by the existing contradiction mediation system can be solved by the scheme provided by the application.
In an optional scheme, the processor further extracts at least one entity element and a logical relationship between the at least one entity element from the dispute description information, determines a node corresponding to the at least one entity element in a dispute knowledge graph based on the logical relationship between the at least one entity element and the at least one entity element, then performs search based on a common neighbor algorithm, determines neighbor nodes of the node, determines a candidate event set based on the node corresponding to the at least one entity element and the neighbor nodes, and finally determines a target event from the candidate event set, and takes the target event as a search result of the dispute event.
In an optional scheme, before determining a node corresponding to at least one entity element in the dispute knowledge graph based on a logical relationship between the at least one entity element and the at least one entity element, the processor further normalizes the logical relationship between the at least one entity element and the at least one entity element to obtain normalized data, and inputs the normalized data to the dispute knowledge graph.
The processor matches at least one entity element and logic relation with data in a preset standard data set, and takes the matched data as standardized data.
Optionally, the dispute event includes a plurality of dispute events, and the dispute description information includes description information of the dispute events.
In an alternative, after determining the set of candidate events, the processor determines the target event from the set of candidate events. Specifically, the processor ranks the candidate events in the candidate event set according to the event type of each candidate event in the candidate event set and the node type corresponding to at least one entity element, and determines the target event based on a preset number of candidate events with the highest rank.
Optionally, the process of the processor sorting the candidate events in the candidate event set according to the event type of each candidate event in the candidate event set and the node type corresponding to the at least one entity element is specifically as follows. The processor determines a first scoring index and a first weight of an event type and a second scoring index and a second weight corresponding to a node type for each candidate event, then determines a final scoring index of each candidate event based on the first scoring index, the first weight, the second scoring index and the second weight, and ranks the candidate events in the candidate event set based on the final scoring index.
In an alternative, the processor may determine the dispute knowledge-graph as follows. Specifically, the processor extracts word features and character features from historical dispute description information, inputs the word features and the character features into a preset learning model for recognition, obtains entity elements of dispute events and logical relations among the entity elements, and finally constructs a dispute knowledge graph based on the entity elements and the logical relations.
Example 4
The embodiment of the application can provide a computer terminal, and the computer terminal can be any one computer terminal device in a computer terminal group. Optionally, in this embodiment, the computer terminal may also be replaced with a terminal device such as a mobile terminal.
Optionally, in this embodiment, the computer terminal may be located in at least one network device of a plurality of network devices of a computer network.
In this embodiment, the computer terminal may execute the program code of the following steps in the dispute event identification method: acquiring dispute description information of dispute events; determining a search result of a dispute event based on dispute description information and a pre-constructed dispute knowledge graph, wherein the dispute knowledge graph at least comprises entity elements in historical dispute description information and a logical relationship between the entity elements in the historical dispute description information; and sending the search result to the user end device.
Optionally, fig. 7 is a block diagram of a computer terminal according to an embodiment of the present application. As shown in fig. 7, the computer terminal a may include: one or more processors 702 (only one of which is shown), a memory 704, and a transmission device 706.
The memory may be configured to store software programs and modules, such as program instructions/modules corresponding to the method and apparatus for identifying a dispute event in the embodiment of the present application, and the processor executes various functional applications and data processing by operating the software programs and modules stored in the memory, so as to implement the method for identifying a dispute event. The memory may include high speed random access memory, and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some examples, the memory may further include memory remotely located from the processor, and these remote memories may be connected to terminal a through a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
The processor can call the information and application program stored in the memory through the transmission device to execute the following steps: acquiring dispute description information of dispute events; determining a search result of a dispute event based on dispute description information and a pre-constructed dispute knowledge graph, wherein the dispute knowledge graph at least comprises entity elements in historical dispute description information and a logical relationship between the entity elements in the historical dispute description information; and sending the search result to the user end device.
Optionally, the processor may further execute the program code of the following steps: extracting at least one entity element and a logical relationship between the at least one entity element from the dispute description information; determining a node corresponding to at least one entity element in the dispute knowledge graph based on the at least one entity element and the logical relationship between the at least one entity element; searching based on a common neighbor algorithm to determine neighbor nodes of the nodes; determining a candidate event set based on a node corresponding to at least one entity element and a neighbor node; and determining a target event from the candidate event set, and taking the target event as a search result of the dispute event.
Optionally, the processor may further execute the program code of the following steps: standardizing at least one entity element and the logic relationship between the at least one entity element to obtain standardized data; and inputting the standardized data into the dispute knowledge graph.
Optionally, the processor may further execute the program code of the following steps: and matching the at least one entity element and the logic relation with the data in the preset standard data set, and taking the matched data as standardized data.
Optionally, the processor may further execute the program code of the following steps: sorting the candidate events in the candidate event set according to the event type of each candidate event in the candidate event set and the node type corresponding to at least one entity element; and determining the target event based on the preset number of the candidate events with the highest ranking.
Optionally, the processor may further execute the program code of the following steps: for each candidate event, determining a first scoring index and a first weight of the event type and a second scoring index and a second weight corresponding to the node type; determining a final scoring index for each candidate event based on the first scoring index, the first weight, the second scoring index, and the second weight; the candidate events in the set of candidate events are ranked based on the final scoring index.
Optionally, the processor may further execute the program code of the following steps: extracting word features and character features from historical dispute description information; inputting the word features and the character features into a preset learning model for recognition to obtain entity elements of dispute events and logic relations among the entity elements; and constructing a dispute knowledge graph based on the entity elements and the logical relationship.
It can be understood by those skilled in the art that the structure shown in fig. 7 is only an illustration, and the computer terminal may also be a terminal device such as a smart phone (e.g., an Android phone, an iOS phone, etc.), a tablet computer, a palmtop computer, a Mobile Internet Device (MID), a PAD, and the like. Fig. 7 is a diagram illustrating a structure of the electronic device. For example, the computer terminal a may also include more or fewer components (e.g., network interfaces, display devices, etc.) than shown in fig. 7, or have a different configuration than shown in fig. 7.
Those skilled in the art will appreciate that all or part of the steps in the methods of the above embodiments may be implemented by a program instructing hardware associated with the terminal device, where the program may be stored in a computer-readable storage medium, and the storage medium may include: flash disks, Read-Only memories (ROMs), Random Access Memories (RAMs), magnetic or optical disks, and the like.
Example 5
Embodiments of the present application also provide a storage medium. Optionally, in this embodiment, the storage medium may be configured to store program codes executed by the method for identifying a dispute event provided in the first embodiment.
Optionally, in this embodiment, the storage medium may be located in any one of computer terminals in a computer terminal group in a computer network, or in any one of mobile terminals in a mobile terminal group.
Optionally, in this embodiment, the storage medium is configured to store program code for performing the following steps: acquiring dispute description information of dispute events; determining a search result of a dispute event based on dispute description information and a pre-constructed dispute knowledge graph, wherein the dispute knowledge graph at least comprises entity elements in historical dispute description information and a logical relationship between the entity elements in the historical dispute description information; and sending the search result to the user end device.
Optionally, in this embodiment, the storage medium is configured to store program code for performing the following steps: extracting at least one entity element and a logical relationship between the at least one entity element from the dispute description information; determining a node corresponding to at least one entity element in the dispute knowledge graph based on the at least one entity element and the logical relationship between the at least one entity element; searching based on a common neighbor algorithm to determine neighbor nodes of the nodes; determining a candidate event set based on a node corresponding to at least one entity element and a neighbor node; and determining a target event from the candidate event set, and taking the target event as a search result of the dispute event.
Optionally, in this embodiment, the storage medium is configured to store program code for performing the following steps: standardizing at least one entity element and the logic relationship between the at least one entity element to obtain standardized data; and inputting the standardized data into the dispute knowledge graph.
Optionally, in this embodiment, the storage medium is configured to store program code for performing the following steps: and matching the at least one entity element and the logic relation with the data in the preset standard data set, and taking the matched data as standardized data.
Optionally, in this embodiment, the storage medium is configured to store program code for performing the following steps: sorting the candidate events in the candidate event set according to the event type of each candidate event in the candidate event set and the node type corresponding to at least one entity element; and determining the target event based on the preset number of the candidate events with the highest ranking.
Optionally, in this embodiment, the storage medium is configured to store program code for performing the following steps: for each candidate event, determining a first scoring index and a first weight of the event type and a second scoring index and a second weight corresponding to the node type; determining a final scoring index for each candidate event based on the first scoring index, the first weight, the second scoring index, and the second weight; the candidate events in the set of candidate events are ranked based on the final scoring index.
Optionally, in this embodiment, the storage medium is configured to store program code for performing the following steps: extracting word features and character features from historical dispute description information; inputting the word features and the character features into a preset learning model for recognition to obtain entity elements of dispute events and logic relations among the entity elements; and constructing a dispute knowledge graph based on the entity elements and the logical relationship.
Example 6
According to an embodiment of the present application, there is also provided a method for identifying a dispute event, such as the flowchart of the method for identifying a dispute event shown in fig. 8, where the method includes the following steps
Step S802, dispute description information of dispute events is obtained.
Alternatively, the dispute events may include, but are not limited to, civil disputes (e.g., property disputes), administrative disputes (e.g., health disputes), legal complaint disputes, and the like. The dispute event description information includes description information of a plurality of dispute events, and the description information of the dispute events includes, but is not limited to, time, place, case-involved persons, and content of the dispute events.
In addition, it should be further noted that the user may input the description information of the dispute event through the user end device, where the user end device may have a plurality of entries, and the user may input the description information of the dispute event through the entries, for example, as shown in a display interface of the user end device shown in fig. 3, the user may input the description information of the dispute event by clicking a "village dispute" control to enter the corresponding interface, or may input the description information of the dispute event by clicking a "noise harassment" control to enter the corresponding interface. Optionally, after the dispute description information of the dispute event is acquired, the server may further store the dispute description information of the dispute event input by the user, where the dispute description information is stored in the data server, or may be stored in a database of the device in which the server is located, and a specific storage location is not limited in the present application.
Step S804, determining a search result of the dispute event based on the dispute description information and a pre-constructed dispute knowledge graph, wherein the dispute knowledge graph at least comprises entity elements in the historical dispute description information and a logical relationship between the entity elements in the historical dispute description information.
It should be noted that the dispute knowledge graph constructed in advance may be stored in the server, and after the dispute description information is obtained, the server uses the dispute description information input by the user as an input of the dispute knowledge graph to obtain a search result of the dispute knowledge graph.
In an alternative scheme, different types of dispute events correspond to different dispute knowledge graphs. After obtaining the dispute description information input by the user, the server determines the dispute type of the dispute event according to the dispute description information, for example, the server extracts a keyword from the dispute description information, and after obtaining the keyword, the server determines the dispute type of the dispute event according to the keyword and the semantics of the context of the keyword, wherein the dispute type of the dispute event includes, but is not limited to, civil dispute, administrative dispute, legal dispute and the like. After the dispute type of the dispute event is determined, the server determines a dispute knowledge graph corresponding to the dispute type according to the dispute type of the dispute event, and further obtains a search result of the dispute event according to the dispute description information and the corresponding dispute knowledge graph.
And step S806, displaying the search result.
It should be noted that the search result of the dispute event may include whether multiple dispute events are the same event and/or which dispute events are the same event.
In an alternative scheme, after obtaining the search result of the dispute event, the user end device may display the search result, where the display form of the search result may include, but is not limited to, text, graphics, and the like. Optionally, the user end device displays the search result to the user in a text form, for example, if the dispute event includes event a and event B, the user end device displays the search result to the user in a form of "event a and event B are the same dispute event". Optionally, when the user end device displays the search result to the user in a graphical form, for example, when there are multiple dispute events, the same dispute event is represented by the same graph or color, and different dispute events are represented by different graphs or colors.
Further, after the search result is displayed to the user, the server can also identify the dispute event, distribute the dispute event identified with the same identification to the terminal of the same responsible person in the same department, process the dispute event by the responsible person, and record the relevant information of the responsible person, so that case-involved persons of the dispute case can inquire the department handling the dispute event, and the handling of the dispute event is more transparent and fair.
Based on the schemes defined in the above steps S802 to S806, it can be known that, after obtaining historical dispute description information of a dispute event by using a mode of identifying the dispute event based on a knowledge graph, determining a search result of the dispute event based on the dispute description information and a pre-constructed dispute knowledge graph, and displaying the search result, wherein the dispute knowledge graph at least includes entity elements in the historical dispute description information and a logical relationship between the entity elements in the historical dispute description information.
It is easy to note that, because the dispute knowledge graph includes the entity elements in the historical dispute description information and the logical relationship between the entity elements, the dispute events reported by the same event through different entries can be automatically identified in a mode based on the dispute knowledge graph, so that the same department can be guaranteed to process the same dispute event, interference of irrelevant information is avoided, and the accuracy of the search result of the dispute event is improved.
Therefore, the technical problem that the dispute event identification is inaccurate by the existing contradiction mediation system can be solved by the scheme provided by the application.
In addition, it should be noted that other relevant contents in this embodiment are the same as those of the embodiment provided in embodiment 1, and are not described herein again.
The above-mentioned serial numbers of the embodiments of the present application are merely for description and do not represent the merits of the embodiments.
In the above embodiments of the present application, the descriptions of the respective embodiments have respective emphasis, and for parts that are not described in detail in a certain embodiment, reference may be made to related descriptions of other embodiments.
In the embodiments provided in the present application, it should be understood that the disclosed technology can be implemented in other ways. The above-described embodiments of the apparatus are merely illustrative, and for example, the division of the units is only one type of division of logical functions, and there may be other divisions when actually implemented, for example, a plurality of units or components may be combined or may be integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, units or modules, and may be in an electrical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.
The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present application may be substantially implemented or contributed to by the prior art, or all or part of the technical solution may be embodied in a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a removable hard disk, a magnetic or optical disk, and other various media capable of storing program codes.
The foregoing is only a preferred embodiment of the present application and it should be noted that those skilled in the art can make several improvements and modifications without departing from the principle of the present application, and these improvements and modifications should also be considered as the protection scope of the present application.
Claims (12)
1. A dispute event identification method is characterized by comprising the following steps:
acquiring dispute description information of dispute events;
determining a search result of the dispute event based on the dispute description information and a pre-constructed dispute knowledge graph, wherein the dispute knowledge graph at least comprises entity elements in historical dispute description information and a logical relationship between the entity elements in the historical dispute description information;
and sending the search result to the user end equipment.
2. The method as claimed in claim 1, wherein determining the search result of the dispute event based on the dispute description information and a pre-constructed dispute knowledge graph comprises:
extracting at least one entity element and a logical relationship between the at least one entity element from the dispute description information;
determining a node corresponding to the at least one entity element in the dispute knowledge graph based on the at least one entity element and the logical relationship between the at least one entity element;
searching based on a common neighbor algorithm, and determining neighbor nodes of the nodes;
determining a candidate event set based on the node corresponding to the at least one entity element and the neighbor node;
and determining a target event from the candidate event set, and taking the target event as a search result of the dispute event.
3. The method of claim 2, wherein prior to determining the node corresponding to the at least one entity element in the dispute knowledge graph based on the logical relationship between the at least one entity element and the at least one entity element, the method further comprises:
standardizing the at least one entity element and the logic relationship between the at least one entity element to obtain standardized data;
and inputting the standardized data into the dispute knowledge graph.
4. The method of claim 3, wherein normalizing the at least one entity element and the logical relationship between the at least one entity element to obtain normalized data comprises:
and matching the at least one entity element and the logic relation with data in a preset standard data set, and taking the matched data as the standardized data.
5. The method according to claim 3, wherein the dispute events are multiple, and the dispute description information includes description information of the dispute events.
6. The method of claim 2, wherein determining a target event from the set of candidate events comprises:
sorting the candidate events in the candidate event set according to the event type of each candidate event in the candidate event set and the node type corresponding to the at least one entity element;
and determining the target event based on the preset number of the candidate events with the highest ranking.
7. The method of claim 6, wherein ranking the candidate events in the candidate event set according to the event type of each candidate event in the candidate event set and the node type corresponding to the at least one entity element comprises:
for each candidate event, determining a first scoring index and a first weight of the event type and a second scoring index and a second weight corresponding to the node type;
determining a final scoring metric for the each candidate event based on the first scoring metric, the first weight, the second scoring metric, and a second weight;
ranking the candidate events in the set of candidate events based on the final scoring index.
8. The method of any one of claims 1 to 7, wherein the dispute knowledge-graph is determined by:
extracting word features and character features from the historical dispute description information;
inputting the word features and the character features into a preset learning model for recognition to obtain the entity elements of the dispute event and the logical relationship between the entity elements;
and constructing the dispute knowledge graph based on the entity elements and the logical relationship.
9. A dispute event identification method is characterized by comprising the following steps:
acquiring dispute description information of dispute events;
determining a search result of the dispute event based on the dispute description information and a pre-constructed dispute knowledge graph, wherein the dispute knowledge graph at least comprises entity elements in historical dispute description information and a logical relationship between the entity elements in the historical dispute description information;
and displaying the search result.
10. An apparatus for identifying a dispute event, comprising:
the dispute management system comprises an acquisition module, a dispute management module and a dispute management module, wherein the acquisition module is used for acquiring dispute description information of dispute events;
the determining module is used for determining a search result of the dispute event based on the dispute description information and a pre-constructed dispute knowledge graph, wherein the dispute knowledge graph at least comprises entity elements in historical dispute description information and a logical relationship between the entity elements in the historical dispute description information;
and the sending module is used for sending the search result to the target object.
11. A dispute event recognition system, comprising: a communication module and a processor; the communication module is used for receiving a query request of a user and sending a search result of the processor to user end equipment;
the processor is configured to acquire dispute description information of a dispute event and a pre-constructed dispute knowledge graph under the trigger of the query request, where the dispute knowledge graph at least includes entity elements in historical dispute description information and a logical relationship between the entity elements in the historical dispute description information; and determining the search result of the dispute event based on the dispute description information and the pre-constructed dispute knowledge graph.
12. A storage medium comprising a stored program, wherein the program, when executed, controls an apparatus on which the storage medium is located to perform the steps of:
acquiring dispute description information of dispute events and a pre-constructed dispute knowledge graph; determining a search result of the dispute event based on the dispute description information and a pre-constructed dispute knowledge graph, wherein the dispute knowledge graph at least comprises entity elements in historical dispute description information and a logical relationship between the entity elements in the historical dispute description information; and sending the search result to the user end equipment.
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Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112182115A (en) * | 2020-09-10 | 2021-01-05 | 珠海格力电器股份有限公司 | Relationship display method and device, storage medium and electronic device |
| CN112269885A (en) * | 2020-11-16 | 2021-01-26 | 北京百度网讯科技有限公司 | Method, apparatus, device and storage medium for processing data |
| CN112508745A (en) * | 2021-02-05 | 2021-03-16 | 北京肇祺信息科技有限公司 | Document evaluation method and device |
| CN113360580A (en) * | 2021-05-31 | 2021-09-07 | 北京百度网讯科技有限公司 | Abnormal event detection method, device, equipment and medium based on knowledge graph |
| CN116469576A (en) * | 2023-03-27 | 2023-07-21 | 中关村科学城城市大脑股份有限公司 | Dispute event identification method, device, electronic equipment and computer readable medium |
Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US8606787B1 (en) * | 2010-09-15 | 2013-12-10 | Google Inc. | Social network node clustering system and method |
| CN104462508A (en) * | 2014-12-19 | 2015-03-25 | 北京奇虎科技有限公司 | Character relation search method and device based on knowledge graph |
| US20160063106A1 (en) * | 2012-08-08 | 2016-03-03 | Google Inc. | Related Entity Search |
| CN106021281A (en) * | 2016-04-29 | 2016-10-12 | 京东方科技集团股份有限公司 | Method for establishing medical knowledge graph, device for same and query method for same |
| CN106776651A (en) * | 2015-11-24 | 2017-05-31 | 阿里巴巴集团控股有限公司 | The processing method and processing device of business dispute |
| US20170270124A1 (en) * | 2016-03-17 | 2017-09-21 | Kabushiki Kaisha Toshiba | Data Management Device, Data Management System, and Data Management Method |
| CN107908671A (en) * | 2017-10-25 | 2018-04-13 | 南京擎盾信息科技有限公司 | Knowledge mapping construction method and system based on law data |
| CN108153901A (en) * | 2018-01-16 | 2018-06-12 | 北京百度网讯科技有限公司 | The information-pushing method and device of knowledge based collection of illustrative plates |
| CN108268582A (en) * | 2017-07-14 | 2018-07-10 | 广东神马搜索科技有限公司 | Information query method and device |
-
2018
- 2018-12-13 CN CN201811528340.6A patent/CN111324740B/en active Active
Patent Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US8606787B1 (en) * | 2010-09-15 | 2013-12-10 | Google Inc. | Social network node clustering system and method |
| US20160063106A1 (en) * | 2012-08-08 | 2016-03-03 | Google Inc. | Related Entity Search |
| CN104462508A (en) * | 2014-12-19 | 2015-03-25 | 北京奇虎科技有限公司 | Character relation search method and device based on knowledge graph |
| CN106776651A (en) * | 2015-11-24 | 2017-05-31 | 阿里巴巴集团控股有限公司 | The processing method and processing device of business dispute |
| US20170270124A1 (en) * | 2016-03-17 | 2017-09-21 | Kabushiki Kaisha Toshiba | Data Management Device, Data Management System, and Data Management Method |
| CN106021281A (en) * | 2016-04-29 | 2016-10-12 | 京东方科技集团股份有限公司 | Method for establishing medical knowledge graph, device for same and query method for same |
| CN108268582A (en) * | 2017-07-14 | 2018-07-10 | 广东神马搜索科技有限公司 | Information query method and device |
| CN107908671A (en) * | 2017-10-25 | 2018-04-13 | 南京擎盾信息科技有限公司 | Knowledge mapping construction method and system based on law data |
| CN108153901A (en) * | 2018-01-16 | 2018-06-12 | 北京百度网讯科技有限公司 | The information-pushing method and device of knowledge based collection of illustrative plates |
Cited By (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112182115A (en) * | 2020-09-10 | 2021-01-05 | 珠海格力电器股份有限公司 | Relationship display method and device, storage medium and electronic device |
| CN112269885A (en) * | 2020-11-16 | 2021-01-26 | 北京百度网讯科技有限公司 | Method, apparatus, device and storage medium for processing data |
| CN112269885B (en) * | 2020-11-16 | 2024-05-10 | 北京百度网讯科技有限公司 | Method, apparatus, device and storage medium for processing data |
| CN112508745A (en) * | 2021-02-05 | 2021-03-16 | 北京肇祺信息科技有限公司 | Document evaluation method and device |
| CN112508745B (en) * | 2021-02-05 | 2021-08-27 | 北京肇祺信息科技有限公司 | Document evaluation method and device |
| CN113360580A (en) * | 2021-05-31 | 2021-09-07 | 北京百度网讯科技有限公司 | Abnormal event detection method, device, equipment and medium based on knowledge graph |
| CN113360580B (en) * | 2021-05-31 | 2023-09-26 | 北京百度网讯科技有限公司 | Abnormal event detection method, device, equipment and medium based on knowledge graph |
| CN116469576A (en) * | 2023-03-27 | 2023-07-21 | 中关村科学城城市大脑股份有限公司 | Dispute event identification method, device, electronic equipment and computer readable medium |
| CN116469576B (en) * | 2023-03-27 | 2023-10-27 | 中关村科学城城市大脑股份有限公司 | Dispute event identification method, device, electronic equipment and computer readable medium |
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