CN112287130A - Searching method, device and equipment for graphic questions - Google Patents
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- CN112287130A CN112287130A CN201910667537.6A CN201910667537A CN112287130A CN 112287130 A CN112287130 A CN 112287130A CN 201910667537 A CN201910667537 A CN 201910667537A CN 112287130 A CN112287130 A CN 112287130A
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- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/40—Information retrieval; Database structures therefor; File system structures therefor of multimedia data, e.g. slideshows comprising image and additional audio data
- G06F16/43—Querying
- G06F16/432—Query formulation
- G06F16/434—Query formulation using image data, e.g. images, photos, pictures taken by a user
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Abstract
The specification discloses a searching method of graphic titles, which comprises the following steps: acquiring a graph of a topic to be searched in a target area; presetting the graph of the question to be searched to obtain a first feature vector; and determining the correct answer of the question to be searched in a database according to the first feature vector. According to the method and the device, the first characteristic vector is obtained by processing the graph of the question to be searched, and the correct answer of the question to be searched is determined according to the first characteristic vector, so that the problem that the question to be searched is difficult to accurately search due to the fact that few characters of the graph question exist in the prior art is solved, and the accuracy rate of searching the graph question is increased.
Description
Technical Field
The present disclosure relates to the field of computer technologies, and in particular, to a method, an apparatus, and a device for searching a graphic topic.
Background
The topic searching technology is that a user can search a topic to be searched and obtain an answer of the topic to be searched through a searching result.
The existing topic searching technology mainly searches the text content of the topic to be searched, but for the graphic topic with few characters, the searching is difficult to be carried out according to the text content, because the graphic topic stores most effective information in the graph, only a few general sentences which do not have the resolution are possible in the extraction, the topic to be searched can be difficult to be accurately searched through the few characters, and the accuracy rate of searching the graphic topic is further influenced.
Disclosure of Invention
The specification provides a searching method, a searching device and searching equipment for graphic titles, and solves the problem that in the prior art, the titles to be searched are difficult to accurately search due to the fact that the number of graphic titles and characters is small.
To solve the above technical problem, the present specification is implemented as follows:
the method for searching graphic titles provided by the specification comprises the following steps:
acquiring a graph of a topic to be searched in a target area;
presetting the graph of the question to be searched to obtain a first feature vector;
and determining the correct answer of the question to be searched in a database according to the first feature vector.
Optionally, the obtaining of the graph of the title to be searched in the target region specifically includes:
and positioning a topic area in the target area according to the identification characteristics, and acquiring the graph of the topic to be searched in the topic area.
Optionally, the identification feature is a printed handwriting feature or a printed shape feature.
Optionally, the obtaining a first feature vector by performing preset processing on the graph of the to-be-searched topic specifically includes:
processing the graph of the title to be searched through an image vectorization model to obtain a second feature vector;
and combining the second characteristic vector with the text content of the title to be searched to obtain the first characteristic vector.
Optionally, the image vectorization model includes a convolutional neural network.
Optionally, the database includes an index database and a content database;
the determining, according to the first feature vector, a correct answer to the question to be searched in a database specifically includes:
matching the first feature vector with the feature vector of the index database to obtain a feature vector with the highest similarity, and determining the question number corresponding to the question to be searched according to the feature vector with the highest similarity;
and searching the standard answer of the question to be searched in the content database according to the question number corresponding to the question to be searched.
The present specification provides a device for searching a graphic topic, the device comprising:
the acquisition unit is used for acquiring a graph of a topic to be searched in a target area;
the processing unit is used for carrying out preset processing on the graph of the title to be searched to obtain a first feature vector;
and the determining unit is used for determining the correct answer of the to-be-searched question in a database according to the first feature vector.
Optionally, the obtaining unit is specifically configured to:
and positioning a topic area in the target area according to the identification characteristics, and acquiring the graph of the topic to be searched in the topic area.
Optionally, the identification feature is a printed handwriting feature or a printed shape feature.
Optionally, the processing unit is specifically configured to:
processing the graph of the title to be searched through an image vectorization model to obtain a second feature vector;
and combining the second characteristic vector with the text content of the title to be searched to obtain the first characteristic vector.
Optionally, the image vectorization model includes a convolutional neural network.
Optionally, the database includes an index database and a content database;
the determining unit is specifically configured to:
matching the first feature vector with the feature vector of the index database to obtain a feature vector with the highest similarity, and determining the question number corresponding to the question to be searched according to the feature vector with the highest similarity;
and searching the standard answer of the question to be searched in the content database according to the question number corresponding to the question to be searched.
The present specification provides a computer readable medium having computer readable instructions stored thereon, the computer readable instructions being executable by a processor to perform the steps of:
acquiring a graph of a topic to be searched in a target area;
presetting the graph of the question to be searched to obtain a first feature vector;
and determining the correct answer of the question to be searched in a database according to the first feature vector.
The present specification provides a search apparatus for graphical subjects, the apparatus comprising a memory for storing computer program instructions and a processor for executing the program instructions, wherein the computer program instructions, when executed by the processor, trigger the apparatus to perform the following:
the acquisition unit is used for acquiring a graph of a topic to be searched in a target area;
the processing unit is used for carrying out preset processing on the graph of the title to be searched to obtain a first feature vector;
and the determining unit is used for determining the correct answer of the to-be-searched question in a database according to the first feature vector.
The embodiment of the specification adopts at least one technical scheme which can achieve the following beneficial effects:
according to the method and the device, the first characteristic vector is obtained by processing the graph of the question to be searched, and the correct answer of the question to be searched is determined according to the first characteristic vector, so that the problem that the question to be searched is difficult to accurately search due to the fact that few characters of the graph question exist in the prior art is solved, and the accuracy rate of searching the graph question is increased.
Drawings
In order to more clearly illustrate the embodiments of the present specification or the technical solutions in the prior art, the drawings needed to be used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments described in the specification, and for those skilled in the art, other drawings can be derived based on the drawings without inventive exercise.
Fig. 1 is a schematic flowchart of a method for searching a graphic topic according to an embodiment of the present disclosure;
fig. 2 is a schematic structural diagram of a searching apparatus for graphic titles provided in the second embodiment of the present specification.
Detailed Description
In order to make those skilled in the art better understand the technical solutions in the present specification, the technical solutions in the embodiments of the present specification will be clearly and completely described below with reference to the drawings in the embodiments of the present specification, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments of the present disclosure without making any creative effort, shall fall within the protection scope of the present disclosure.
Fig. 1 is a schematic flow chart of a method for searching a graphic topic provided in an embodiment of the present specification, where the schematic flow chart includes:
step S101, obtaining a graph of a topic to be searched in a target area.
In step S101 in the embodiment of this specification, acquiring a graphic of a topic to be searched in a target region may specifically include the following steps: positioning a question area in a target area according to a first identification characteristic, and acquiring a picture of a question to be searched in the question area, wherein the first identification characteristic is a printing handwriting characteristic or a printing shape characteristic, the target area can be a certain question to be searched, the area containing the printing handwriting characteristic or the printing shape characteristic is determined as the target area, an image of the target area can be acquired through image acquisition equipment, and the picture of the question to be searched is acquired in the image of the target area; or, the target area may also be an entire test paper to be searched, successively positioning an area containing the print handwriting characteristics or the print shape characteristics, determining the area containing the print handwriting characteristics or the print shape characteristics as the target area, and respectively acquiring the graph of each topic to be searched in the image of the target area.
And S102, carrying out preset processing on the graph of the title to be searched to obtain a first feature vector.
In step S101 in the embodiment of this specification, the graph of the title to be searched is subjected to preset processing to obtain a first feature vector, and the specific steps may be as follows:
processing the graph of the title to be searched through an image vectorization model to obtain a second feature vector, wherein the image vectorization model comprises a convolutional neural network;
and combining the second characteristic vector with the text content of the title to be searched to obtain the first characteristic vector.
And S103, determining the correct answer of the question to be searched in a database according to the first feature vector.
In step S103 of the embodiment of the present specification, the database includes an index database and a content database, and the database may be applied in an offline state.
In step S103 in the embodiment of this specification, determining a correct answer to the question to be searched in a database according to the first feature vector may specifically include the following steps:
matching the first feature vector with the feature vector of the index database to obtain a feature vector with the highest similarity, and determining the question number corresponding to the question to be searched according to the feature vector with the highest similarity; and searching the standard answer of the question to be searched in the content database according to the question number corresponding to the question to be searched. The index database and the content database are linked by using a unique title number, wherein: the content database comprises information of the content, answers, knowledge point analysis and the like of all graphic questions; the index database comprises first characteristic vectors of all graphic topics, and the first characteristic vectors can be formed by combining the characteristic vectors extracted by the image vectorization model and the text contents of the topics.
In the method for searching a graphic topic provided by the embodiment, a user can photograph the graphic topic through an image acquisition device, and finally, a solution of the graphic topic, high-quality knowledge point analysis and the like are obtained.
With the development of the internet and communication technology, the graphic questions are collected through the graphic collection device, and then reference answers and knowledge point analysis of the graphic questions are searched out, so that the method becomes a favorable means for improving learning efficiency and tutoring quality. The embodiment breaks through the technical bottleneck that graphic topics are difficult to search in the prior art, provides a complete solution for searching the graphic topics, and enables answers and high-quality knowledge point analysis of the graphic topics to be better transmitted to users.
According to the method and the device, the first characteristic vector is obtained by processing the graph of the question to be searched, and the correct answer of the question to be searched is determined according to the first characteristic vector, so that the problem that the question to be searched is difficult to accurately search due to the fact that few characters of the graph question exist in the prior art is solved, and the accuracy rate of searching the graph question is increased.
Fig. 2 is a schematic structural diagram of a searching apparatus for a graphic topic provided in the second embodiment of the present specification, where the schematic structural diagram includes: the device comprises an acquisition unit 1, a processing unit 2 and a determination unit 3.
The obtaining unit 1 is configured to obtain a graphic of a topic to be searched in a target region.
The processing unit 2 is configured to perform preset processing on the graph of the topic to be searched to obtain a first feature vector.
The determining unit 3 is configured to determine, according to the first feature vector, a correct answer to the question to be searched in a database.
The obtaining unit 1 is specifically configured to:
and positioning a topic area in the target area according to the identification characteristics, and acquiring the graph of the topic to be searched in the topic area.
The identification feature is a print script feature or a print shape feature.
The processing unit 2 is specifically configured to:
processing the graph of the title to be searched through an image vectorization model to obtain a second feature vector;
and combining the second characteristic vector with the text content of the title to be searched to obtain the first characteristic vector.
The image vectorization model includes a convolutional neural network.
The database comprises an index database and a content database;
the determining unit 3 is specifically configured to:
matching the first feature vector with the feature vector of the index database to obtain a feature vector with the highest similarity, and determining the question number corresponding to the question to be searched according to the feature vector with the highest similarity;
and searching the standard answer of the question to be searched in the content database according to the question number corresponding to the question to be searched.
According to the invention, the processing unit processes the graph of the question to be searched to obtain the first feature vector, and the determining unit determines the correct answer of the question to be searched according to the first feature vector, so that the problem that the question to be searched is difficult to accurately search due to less graph questions and characters in the prior art is solved, and the accuracy rate of searching the graph question is increased.
The present specification provides a computer readable medium having computer readable instructions stored thereon, the computer readable instructions being executable by a processor to perform the steps of:
acquiring a graph of a topic to be searched in a target area;
presetting the graph of the question to be searched to obtain a first feature vector;
and determining the correct answer of the question to be searched in a database according to the first feature vector.
The invention obtains the first characteristic vector by processing the graph of the question to be searched, and then determines the correct answer of the question to be searched according to the first characteristic vector, thereby solving the problem that the question to be searched is difficult to accurately search due to less graph question characters in the prior art, and further increasing the accuracy rate of searching the graph question
The present specification provides a search apparatus for graphical subjects, the apparatus comprising a memory for storing computer program instructions and a processor for executing the program instructions, wherein the computer program instructions, when executed by the processor, trigger the apparatus to perform the following:
the acquisition unit is used for acquiring a graph of a topic to be searched in a target area;
the processing unit is used for carrying out preset processing on the graph of the title to be searched to obtain a first feature vector;
and the determining unit is used for determining the correct answer of the to-be-searched question in a database according to the first feature vector.
The invention obtains the first characteristic vector by processing the graph of the question to be searched, and then determines the correct answer of the question to be searched according to the first characteristic vector, thereby solving the problem that the question to be searched is difficult to accurately search due to less graph question characters in the prior art, and further increasing the accuracy rate of searching the graph question
In the 90 s of the 20 th century, improvements in a technology could clearly distinguish between improvements in hardware (e.g., improvements in circuit structures such as diodes, transistors, switches, etc.) and improvements in software (improvements in process flow). However, as technology advances, many of today's process flow improvements have been seen as direct improvements in hardware circuit architecture. Designers almost always obtain the corresponding hardware circuit structure by programming an improved method flow into the hardware circuit. Thus, it cannot be said that an improvement in the process flow cannot be realized by hardware physical modules. For example, a Programmable Logic Device (PLD), such as a Field Programmable Gate Array (FPGA), is an integrated circuit whose logic functions are determined by programming the device by a user. A digital system is "integrated" on a PLD by the designer's own programming without requiring the chip manufacturer to design and fabricate application-specific integrated circuit chips. Furthermore, nowadays, instead of manually manufacturing an integrated circuit chip, such programming is mostly implemented by "logic compiler" software, which is similar to a software compiler used in program development and writing, but the original code before compiling is also written by a specific programming Language, which is called Hardware Description Language (HDL), and the HDL is not only one but many, and it should be clear to those skilled in the art that the Hardware circuit for implementing the logic method flow can be easily obtained by only slightly programming the logic of the method flow in the above Hardware Description languages and programming the integrated circuit.
The controller may be implemented in any suitable manner, for example, the controller may take the form of, for example, a microprocessor or processor and a computer-readable medium storing computer-readable program code (e.g., software or firmware) executable by the (micro) processor, logic gates, switches, an Application Specific Integrated Circuit (ASIC), a programmable logic controller, and an embedded microcontroller, examples of which include, but are not limited to, the following microcontrollers: ARC 625D, Atmel AT91SAM, Microchip PIC18F26K20, and Silicone Labs C8051F320, the memory controller may also be implemented as part of the control logic for the memory. Those skilled in the art will also appreciate that, in addition to implementing the controller as pure computer readable program code, the same functionality can be implemented by logically programming method steps such that the controller is in the form of logic gates, switches, application specific integrated circuits, programmable logic controllers, embedded microcontrollers and the like. Such a controller may thus be considered a hardware component, and the means included therein for performing the various functions may also be considered as a structure within the hardware component. Or even means for performing the functions may be regarded as being both a software module for performing the method and a structure within a hardware component.
The systems, devices, modules or units illustrated in the above embodiments may be implemented by a computer chip or an entity, or by a product with certain functions. One typical implementation device is a computer. In particular, the computer may be, for example, a personal computer, a laptop computer, a cellular telephone, a camera phone, a smartphone, a personal digital assistant, a media player, a navigation device, an email device, a game console, a tablet computer, a wearable device, or a combination of any of these devices.
For convenience of description, the above devices are described as being divided into various units by function, and are described separately. Of course, the functionality of the units may be implemented in one or more software and/or hardware when implementing the present application.
As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
In a typical configuration, a computing device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory.
The memory may include forms of volatile memory in a computer readable medium, Random Access Memory (RAM) and/or non-volatile memory, such as Read Only Memory (ROM) or flash memory (flash RAM). Memory is an example of a computer-readable medium.
Computer-readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), Read Only Memory (ROM), Electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), Digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information that can be accessed by a computing device. As defined herein, a computer readable medium does not include a transitory computer readable medium such as a modulated data signal and a carrier wave.
It should also be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.
The application may be described in the general context of computer-executable instructions, such as program modules, being executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform particular tasks or implement particular abstract data types. The application may also be practiced in distributed computing environments where tasks are performed by remote processing devices that are linked through a communications network. In a distributed computing environment, program modules may be located in both local and remote computer storage media including memory storage devices.
The embodiments in the present specification are described in a progressive manner, and the same and similar parts among the embodiments are referred to each other, and each embodiment focuses on the differences from the other embodiments. In particular, for the system embodiment, since it is substantially similar to the method embodiment, the description is simple, and for the relevant points, reference may be made to the partial description of the method embodiment.
The above description is only an example of the present application and is not intended to limit the present application. Various modifications and changes may occur to those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the scope of the claims of the present application.
Claims (10)
1. A method for searching graphic titles, the method comprising:
acquiring a graph of a topic to be searched in a target area;
presetting the graph of the question to be searched to obtain a first feature vector;
and determining the correct answer of the question to be searched in a database according to the first feature vector.
2. The method for searching graphic topics according to claim 1, wherein the obtaining of the graphic of the topic to be searched in the target region specifically comprises:
and positioning a topic area in the target area according to the identification characteristics, and acquiring the graph of the topic to be searched in the topic area.
3. A method for searching for a graphic title as claimed in claim 2, wherein the identification feature is a print script feature or a print shape feature.
4. The method for searching graphic topics according to claim 1, wherein the obtaining of the first feature vector by pre-processing the graphic of the topic to be searched specifically comprises:
processing the graph of the title to be searched through an image vectorization model to obtain a second feature vector;
and combining the second characteristic vector with the text content of the title to be searched to obtain the first characteristic vector.
5. The method of searching for graphic topics of claim 4, wherein the image vectorization model comprises a convolutional neural network.
6. The method of searching for graphic topics of claim 1, wherein the database comprises an index database and a content database;
the determining, according to the first feature vector, a correct answer to the question to be searched in a database specifically includes:
matching the first feature vector with the feature vector of the index database to obtain a feature vector with the highest similarity, and determining the question number corresponding to the question to be searched according to the feature vector with the highest similarity;
and searching the standard answer of the question to be searched in the content database according to the question number corresponding to the question to be searched.
7. An apparatus for searching a graphic topic, the apparatus comprising:
the acquisition unit is used for acquiring a graph of a topic to be searched in a target area;
the processing unit is used for carrying out preset processing on the graph of the title to be searched to obtain a first feature vector;
and the determining unit is used for determining the correct answer of the to-be-searched question in a database according to the first feature vector.
8. The apparatus for searching for graphic topics according to claim 7, wherein the obtaining unit is specifically configured to:
and positioning a topic area in the target area according to the identification characteristics, and acquiring the graph of the topic to be searched in the topic area.
9. A search apparatus for a graphic title, the apparatus comprising a memory for storing computer program instructions and a processor for executing the program instructions, wherein the computer program instructions, when executed by the processor, trigger the apparatus to perform the apparatus of any of claims 7-8.
10. A computer readable medium having computer readable instructions stored thereon, the computer readable instructions being executable by a processor to perform the method of any one of claims 1-6.
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| CN201910667537.6A CN112287130A (en) | 2019-07-23 | 2019-07-23 | Searching method, device and equipment for graphic questions |
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| CN201910667537.6A CN112287130A (en) | 2019-07-23 | 2019-07-23 | Searching method, device and equipment for graphic questions |
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