CN111475536A - Data analysis method and device based on search engine - Google Patents
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Abstract
The application provides a data analysis method and device based on a search engine, wherein the method comprises the following steps: the method comprises the steps of obtaining keywords input by a user, carrying out word expansion processing on the keywords to generate a plurality of related keywords, carrying out aggregation processing on the related keywords to generate a keyword data packet, inquiring in a preset search database according to the keyword data packet to obtain search data corresponding to the keyword data packet, and finally analyzing the keywords according to the search data. Therefore, the mining of the real requirements of the user is improved, the target things can be accurately predicted, and the user experience is improved.
Description
Technical Field
The present application relates to the field of internet technologies, and in particular, to a data analysis method and apparatus based on a search engine.
Background
With the development of the internet technology, a user can search through a search engine to obtain a corresponding result according to the requirement. That is, the search data can reflect the real needs of the user in daily life, however, the existing search data can only analyze the current and historical data, so that the mining of the real needs of the user is greatly reduced, and the hysteresis of most things is caused.
Disclosure of Invention
The present application is directed to solving, at least to some extent, one of the technical problems in the related art.
Therefore, the data analysis method and device based on the search engine are provided by the application and used for solving the technical problems that the existing search data in the prior art only can analyze the current and historical data, the mining on the real requirements of users is greatly reduced, and the hysteresis of most things is caused.
In order to achieve the above object, an embodiment of a first aspect of the present application provides a data analysis method based on a search engine, including:
acquiring a keyword input by a user, and carrying out word expansion processing on the keyword to generate a plurality of related keywords;
performing aggregation processing on the plurality of related keywords to generate a keyword data packet;
inquiring in a preset search database according to the keyword data packet to obtain search data corresponding to the keyword data packet;
and analyzing the keywords according to the search data.
According to the data analysis method based on the search engine, the keywords input by the user are obtained, word expansion processing is conducted on the keywords to generate the plurality of related keywords, the plurality of related keywords are aggregated to generate the keyword data packet, query is conducted in the preset search database according to the keyword data packet to obtain the search data corresponding to the keyword data packet, and finally the keywords are analyzed according to the search data. Therefore, the mining of the real requirements of the user is improved, the target things can be accurately predicted, and the user experience is improved.
In order to achieve the above object, a second aspect of the present application provides a data analysis apparatus based on a search engine, including:
the system comprises a first acquisition module, a second acquisition module and a processing module, wherein the first acquisition module is used for acquiring the current submission time interval and the current submission times of a user account to be intercepted;
the first acquisition module is used for acquiring keywords input by a user and carrying out word expansion processing on the keywords to generate a plurality of related keywords;
the aggregation module is used for performing aggregation processing on the plurality of related keywords to generate a keyword data packet;
the query module is used for querying in a preset search database according to the keyword data packet to acquire search data corresponding to the keyword data packet;
and the analysis module is used for analyzing the keywords according to the search data.
According to the data analysis device based on the search engine, the keywords input by the user are obtained, word expansion processing is carried out on the keywords to generate the plurality of related keywords, the plurality of related keywords are aggregated to generate the keyword data packet, query is carried out in the preset search database according to the keyword data packet to obtain the search data corresponding to the keyword data packet, and finally the keywords are analyzed according to the search data. Therefore, the mining of the real requirements of the user is improved, the target things can be accurately predicted, and the user experience is improved.
To achieve the above object, a third aspect of the present application provides a computer device, including: a processor and a memory; wherein the processor executes a program corresponding to the executable program code by reading the executable program code stored in the memory, so as to implement the data analysis method based on the search engine as described in the embodiment of the first aspect.
To achieve the above object, a fourth aspect of the present application provides a non-transitory computer-readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor, implements a search engine-based data analysis method according to the first aspect.
To achieve the above object, a fifth aspect of the present application provides a computer program product, where instructions of the computer program product, when executed by a processor, implement a search engine-based data analysis method as described in the first aspect of the present application.
Additional aspects and advantages of the present application will be set forth in part in the description which follows and, in part, will be obvious from the description, or may be learned by practice of the present application.
Drawings
The foregoing and/or additional aspects and advantages of the present application will become apparent and readily appreciated from the following description of the embodiments, taken in conjunction with the accompanying drawings of which:
fig. 1 is a schematic flowchart of a data analysis method based on a search engine according to an embodiment of the present application;
FIG. 2 is a schematic diagram of generating a default search database provided by an embodiment of the present application;
3 a-3 b are schematic diagrams of keyword analysis according to search data provided by an embodiment of the present application;
fig. 4 is a schematic structural diagram of a data analysis apparatus based on a search engine according to an embodiment of the present application;
FIG. 5 is a schematic structural diagram of another search engine-based data analysis apparatus according to an embodiment of the present application; and
fig. 6 is a schematic structural diagram of a computer device according to an embodiment of the present application.
Detailed Description
Reference will now be made in detail to embodiments of the present application, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to the same or similar elements or elements having the same or similar function throughout. The embodiments described below with reference to the drawings are exemplary and intended to be used for explaining the present application and should not be construed as limiting the present application.
A search engine-based data analysis method and apparatus according to an embodiment of the present application are described below with reference to the accompanying drawings.
Fig. 1 is a schematic flowchart of a data analysis method based on a search engine according to an embodiment of the present disclosure.
As shown in fig. 1, the search engine-based data analysis method may include the steps of:
In practical application, a user can input corresponding search sentences according to practical application requirements, such as "how the mobile phone is in shape", "house price", and the like, so that the search sentences input by the user can be directly used as keywords input by the user, such as "house price" as keywords input by the user, and keywords extracted by performing word segmentation processing on the search sentences can also be used as keywords input by the user, such as "how the mobile phone is in shape" as "what the mobile phone is in shape" and "what the mobile phone is in shape", and "what the mobile phone is in shape" as keywords input by the user.
After keywords input by a user are obtained, word expansion processing is carried out on the keywords to generate a plurality of related keywords, for example, the keywords are 'cold', word expansion processing is carried out on 'cold', so that 'how fast the cold is eaten', 'how does the pregnant woman is cold', 'how fast the cold is coughed,', 'wind-cold type cold', 'cold cough', 'what medicine is eaten by the wind-cold type cold', 'cold medicine', 'wind-heat type cold', 'wind-cold type cold symptom' and 'how does the cold is in lactation' and the like can be obtained, and then the related keywords are extracted from a plurality of sentences after word expansion processing, for example, 'cold', 'cold cough', and 'wind-cold type cold'.
And 102, aggregating the plurality of related keywords to generate a keyword data packet.
And 103, inquiring in a preset search database according to the keyword data packet to acquire search data corresponding to the keyword data packet.
After a plurality of related keywords are generated, aggregation processing can be performed on the related keywords to generate a keyword data packet, that is, the related keywords are stored in one data packet, so that the keyword data packet can be subsequently queried in a preset search database to obtain search data corresponding to the keyword data packet.
It is understood that, as one possible implementation, the generating of the search database in advance, as shown in fig. 2, includes:
Specifically, search keywords input by a plurality of users in the period from 1996 to 2018 can be acquired, search time, search modes, search user account attributions and the like corresponding to the search keywords are recorded, such as the search keyword "cold", which is obtained by analyzing the search time and the search user account attributions of the search keywords, which corresponds to the search keywords and which is more in each year, which is more in each year and which is more in each attribution, and the like, so that the search time, the search region, the search type and the like of the keywords are classified and stored, and a preset search database is generated.
The search data may be one or more of search time data, search area data, and search type data.
And 104, analyzing the keywords according to the search data.
It is understood that the results of analyzing the keywords by different search data are different, for example, as follows:
in a first example, searching data includes: searching time data and searching region data, determining the prediction time corresponding to the keyword according to the searching time data, determining the prediction region corresponding to the keyword according to the searching region data, and displaying the prediction time and the prediction region to a user.
For example, the keyword "cold" generates a plurality of related keywords "cold", "cold cough" and "wind-cold" and performs aggregation processing to generate a keyword data packet, "cold + cold cough + wind-cold" for querying in a preset search database, and obtains search data corresponding to the keyword data packet, such as search time data shown in fig. 3a and search region data shown in fig. 3 b. Therefore, the prediction time corresponding to the cold can be determined to be 12 months and 1 month every year according to the search time data, the prediction region corresponding to the cold is determined to be the south China east China, and the south China east China, which predicts the 12 months and 1 month in the next year, is also the high-incidence stage of the cold, so that the advanced prevention and preparation work can be carried out.
In a second example, searching data includes: searching type data and searching region data, determining a prediction type corresponding to the keyword according to the searching type data, determining a prediction region corresponding to the keyword according to the searching region data, and displaying the prediction type and the prediction region to a user.
For example, a keyword "car" generates a plurality of related keywords "car", "new energy car" and "electric car" and performs aggregation processing to generate a keyword data packet "car + new energy car + electric car" to query in a preset search database, and search data corresponding to the keyword data packet is obtained, so that the prediction type corresponding to "car" can be determined to be the electric car according to the search type data, the prediction region corresponding to "car" can be determined to be a large city such as beijing, shanghai and the like according to the search region data, sales quantity of electric cars of the large cities such as beijing, shanghai and the like for predicting the next year can be increased, and research and production of the electric cars of the cities can be increased.
In a third example, searching for data includes: searching the prompt data and the search region data, determining prompt information corresponding to the keywords according to the search prompt data, determining a prediction region corresponding to the keywords according to the search region data, and displaying the prompt information and the prediction region to a user.
For example, a keyword "protect animal" generates a plurality of related keywords "protect animal", "critical animal" and "extinct animal" to perform aggregation processing to generate a keyword data packet, "protect animal + critical animal + extinct animal" to perform query in a preset search database, and obtain search data corresponding to the keyword data packet, so that prompt information corresponding to the "protect animal" can be determined as enhanced protection according to search prompt data, a prediction region corresponding to the "protect animal" is determined as a south China region according to search region data, the protection animal in the south China region in the future can be predicted to be enhanced protection, possible damage can be avoided, and biological protection can be assisted.
In the data analysis method based on the search engine of this embodiment, the keywords input by the user are obtained, the keywords are subjected to word expansion processing to generate a plurality of related keywords, the related keywords are subjected to aggregation processing to generate a keyword data packet, a query is performed in a preset search database according to the keyword data packet to obtain search data corresponding to the keyword data packet, and finally, the keywords are analyzed according to the search data. Therefore, the mining of the real requirements of the user is improved, the target things can be accurately predicted, and the user experience is improved.
In order to implement the above embodiments, the present application further provides a data analysis device based on a search engine.
Fig. 4 is a schematic structural diagram of a data analysis apparatus based on a search engine according to an embodiment of the present application.
As shown in fig. 4, the search engine-based data analysis apparatus may include: a first acquisition module 410, an aggregation module 420, a query module 430, and an analysis module 440. Wherein the content of the first and second substances,
the first obtaining module 410 is configured to obtain a keyword input by a user, and perform word expansion processing on the keyword to generate a plurality of related keywords.
And the aggregation module 420 is configured to aggregate the plurality of related keywords to generate a keyword data packet.
The query module 430 is configured to query the preset search database according to the keyword data packet, and obtain search data corresponding to the keyword data packet.
And an analysis module 440, configured to analyze the keyword according to the search data.
In a possible implementation manner of the embodiment of the present application, as shown in fig. 5, on the basis of fig. 4, the method further includes: a second acquisition module 450 and a generation module 460.
The second obtaining module 450 is configured to obtain the search keywords input by the user in different time periods.
The generating module 460 is configured to analyze the plurality of search keywords, store the search keywords in a preset manner, and generate a preset search database.
In one possible implementation manner of the embodiment of the present application, the searching for data includes: searching time data and searching region data; the analysis module 440 is specifically configured to: determining the corresponding prediction time of the keyword according to the search time data; determining a prediction region corresponding to the keyword according to the search region data; and displaying the predicted time and the predicted region to the user.
In one possible implementation manner of the embodiment of the present application, the searching for data includes: searching type data and searching region data; the analysis module 440 is specifically configured to: determining a prediction type corresponding to the keyword according to the search type data; determining a prediction region corresponding to the keyword according to the search region data; and displaying the prediction type and the prediction region to a user.
In one possible implementation manner of the embodiment of the present application, the searching for data includes: searching prompt data and searching region data; the analysis module 440 is specifically configured to: determining prompt information corresponding to the keywords according to the search prompt data; determining a prediction region corresponding to the keyword according to the search region data; and displaying the prompt information and the prediction region to the user.
It should be noted that the foregoing explanation of the embodiment of the data analysis method based on the search engine is also applicable to the data analysis apparatus based on the search engine of the embodiment, and the implementation principle thereof is similar, and is not repeated here.
According to the data analysis device based on the search engine, the keywords input by the user are obtained, word expansion processing is carried out on the keywords to generate the plurality of related keywords, the plurality of related keywords are aggregated to generate the keyword data packet, query is carried out in the preset search database according to the keyword data packet to obtain the search data corresponding to the keyword data packet, and finally the keywords are analyzed according to the search data. Therefore, the mining of the real requirements of the user is improved, the target things can be accurately predicted, and the user experience is improved.
By in order to implement the above embodiments, the present application also provides a computer device, including: a processor and a memory. Wherein the processor executes a program corresponding to the executable program code by reading the executable program code stored in the memory, for implementing the search engine-based data analysis method as described in the foregoing embodiments.
FIG. 6 is a block diagram of a computer device provided in an embodiment of the present application, illustrating an exemplary computer device 90 suitable for use in implementing embodiments of the present application. The computer device 90 shown in fig. 6 is only an example, and should not bring any limitation to the function and the scope of use of the embodiments of the present application.
As shown in fig. 6, the computer device 90 is in the form of a general purpose computer device. The components of computer device 90 may include, but are not limited to: one or more processors or processing units 906, a system memory 910, and a bus 908 that couples the various system components (including the system memory 910 and the processing unit 906).
The system Memory 910 may include computer system readable media in the form of volatile Memory, such as Random Access Memory (RAM) 911 and/or cache Memory 912. The computer device 90 may further include other removable/non-removable, volatile/nonvolatile computer system storage media. By way of example only, storage system 913 may be used to read from and write to non-removable, nonvolatile magnetic media (not shown in FIG. 6, and commonly referred to as a "hard disk drive"). Although not shown in FIG. 6, a disk drive for reading from and writing to a removable, nonvolatile magnetic disk (e.g., a "floppy disk") and an optical disk drive for reading from or writing to a removable, nonvolatile optical disk (e.g., a Compact disk Read Only Memory (CD-ROM), a Digital versatile disk Read Only Memory (DVD-ROM), or other optical media) may be provided. In these cases, each drive may be connected to bus 908 by one or more data media interfaces. System memory 910 may include at least one program product having a set (e.g., at least one) of program modules that are configured to carry out the functions of embodiments of the application.
A computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take any of a variety of forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device.
Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.
Computer program code for carrying out operations for aspects of the present application may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, Smalltalk, C + +, and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server.
Program/utility 914 having a set (at least one) of program modules 9140 may be stored, for example, in system memory 910, such program modules 9140 including, but not limited to, an operating system, one or more application programs, other program modules, and program data, each of which or some combination of these examples may comprise an implementation of a network environment. Program modules 9140 generally perform the functions and/or methods of embodiments described herein.
The processing unit 906 executes various functional applications and search engine-based data analysis by executing programs stored in the system memory 910, for example, implementing the search engine-based data analysis method mentioned in the foregoing embodiments.
In order to implement the above embodiments, the present application also proposes a non-transitory computer-readable storage medium on which a computer program is stored, which when executed by a processor, implements the search engine-based data analysis method as described in the foregoing embodiments.
In order to implement the foregoing embodiments, the present application also proposes a computer program product, wherein when the instructions of the computer program product are executed by a processor, the search engine-based data analysis method as described in the foregoing embodiments is implemented.
In the description herein, reference to the description of the term "one embodiment," "some embodiments," "an example," "a specific example," or "some examples," etc., means that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the application. In this specification, the schematic representations of the terms used above are not necessarily intended to refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples. Furthermore, various embodiments or examples and features of different embodiments or examples described in this specification can be combined and combined by one skilled in the art without contradiction.
Furthermore, the terms "first", "second" and "first" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one such feature. In the description of the present application, "plurality" means at least two, e.g., two, three, etc., unless specifically limited otherwise.
Any process or method descriptions in flow charts or otherwise described herein may be understood as representing modules, segments, or portions of code which include one or more executable instructions for implementing steps of a custom logic function or process, and alternate implementations are included within the scope of the preferred embodiment of the present application in which functions may be executed out of order from that shown or discussed, including substantially concurrently or in reverse order, depending on the functionality involved, as would be understood by those reasonably skilled in the art of the present application.
The logic and/or steps represented in the flowcharts or otherwise described herein, e.g., an ordered listing of executable instructions that can be considered to implement logical functions, can be embodied in any computer-readable medium for use by or in connection with an instruction execution system, apparatus, or device, such as a computer-based system, processor-containing system, or other system that can fetch the instructions from the instruction execution system, apparatus, or device and execute the instructions. For the purposes of this description, a "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transport the program for use by or in connection with the instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of the computer-readable medium would include the following: an electrical connection (electronic device) having one or more wires, a portable computer diskette (magnetic device), a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disc read-only memory (CDROM). Additionally, the computer-readable medium could even be paper or another suitable medium upon which the program is printed, as the program can be electronically captured, via for instance optical scanning of the paper or other medium, then compiled, interpreted or otherwise processed in a suitable manner if necessary, and then stored in a computer memory.
It should be understood that portions of the present application may be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, the various steps or methods may be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. If implemented in hardware, as in another embodiment, any one or combination of the following techniques, which are known in the art, may be used: a discrete logic circuit having a logic gate circuit for implementing a logic function on a data signal, an application specific integrated circuit having an appropriate combinational logic gate circuit, a Programmable Gate Array (PGA), a Field Programmable Gate Array (FPGA), or the like.
It will be understood by those skilled in the art that all or part of the steps carried by the method for implementing the above embodiments may be implemented by hardware related to instructions of a program, which may be stored in a computer readable storage medium, and when the program is executed, the program includes one or a combination of the steps of the method embodiments.
In addition, functional units in the embodiments of the present application may be integrated into one processing module, or each unit may exist alone physically, or two or more units are integrated into one module. The integrated module can be realized in a hardware mode, and can also be realized in a software functional module mode. The integrated module, if implemented in the form of a software functional module and sold or used as a stand-alone product, may also be stored in a computer readable storage medium.
The storage medium mentioned above may be a read-only memory, a magnetic or optical disk, etc. Although embodiments of the present application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present application, and that variations, modifications, substitutions and alterations may be made to the above embodiments by those of ordinary skill in the art within the scope of the present application.
Claims (12)
1. A data analysis method based on a search engine is characterized by comprising the following steps:
acquiring a keyword input by a user, and carrying out word expansion processing on the keyword to generate a plurality of related keywords;
performing aggregation processing on the plurality of related keywords to generate a keyword data packet;
inquiring in a preset search database according to the keyword data packet to obtain search data corresponding to the keyword data packet;
and analyzing the keywords according to the search data.
2. The method of claim 1, further comprising, prior to said querying in a predetermined search database according to said keyword data package:
acquiring search keywords input by a user in different time periods;
and analyzing the plurality of search keywords, storing the search keywords according to a preset mode, and generating a preset search database.
3. The method of claim 1, wherein the searching the data comprises: searching time data and searching region data;
the analyzing the keywords according to the search data includes:
determining the prediction time corresponding to the keyword according to the search time data;
determining a prediction region corresponding to the keyword according to the search region data;
and displaying the predicted time and the predicted region to the user.
4. The method of claim 1, wherein the searching the data comprises: searching type data and searching region data;
the analyzing the keywords according to the search data includes:
determining a prediction type corresponding to the keyword according to the search type data;
determining a prediction region corresponding to the keyword according to the search region data;
and displaying the prediction type and the prediction region to the user.
5. The method of claim 1, wherein the searching the data comprises: searching prompt data and searching region data;
the analyzing the keywords according to the search data includes:
determining prompt information corresponding to the keyword according to the search prompt data;
determining a prediction region corresponding to the keyword according to the search region data;
and displaying the prompt information and the prediction region to the user.
6. A search engine based data analysis apparatus, comprising:
the first acquisition module is used for acquiring keywords input by a user and carrying out word expansion processing on the keywords to generate a plurality of related keywords;
the aggregation module is used for performing aggregation processing on the plurality of related keywords to generate a keyword data packet;
the query module is used for querying in a preset search database according to the keyword data packet to acquire search data corresponding to the keyword data packet;
and the analysis module is used for analyzing the keywords according to the search data.
7. The apparatus of claim 6, further comprising:
the second acquisition module is used for acquiring search keywords input by a user in different time periods;
and the generating module is used for analyzing the plurality of search keywords, storing the search keywords according to a preset mode and generating a preset search database.
8. The apparatus of claim 6, wherein the search data comprises: searching time data and searching region data;
the analysis module is specifically configured to:
determining the prediction time corresponding to the keyword according to the search time data;
determining a prediction region corresponding to the keyword according to the search region data;
and displaying the predicted time and the predicted region to the user.
9. The apparatus of claim 6, wherein the search data comprises: searching type data and searching region data;
the analysis module is specifically configured to:
determining a prediction type corresponding to the keyword according to the search type data;
determining a prediction region corresponding to the keyword according to the search region data;
and displaying the prediction type and the prediction region to the user.
10. The apparatus of claim 6, wherein the search data comprises: searching prompt data and searching region data;
the analysis module is specifically configured to:
determining prompt information corresponding to the keyword according to the search prompt data;
determining a prediction region corresponding to the keyword according to the search region data;
and displaying the prompt information and the prediction region to the user.
11. A computer device comprising a processor and a memory;
wherein the processor executes a program corresponding to the executable program code by reading the executable program code stored in the memory for implementing the search engine-based data analysis method according to any one of claims 1 to 5.
12. A non-transitory computer readable storage medium having stored thereon a computer program, wherein the program, when executed by a processor, implements a search engine based data analysis method according to any one of claims 1-5.
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Citations (15)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2008098467A1 (en) * | 2007-02-15 | 2008-08-21 | Erzhong Liu | Convenient method and system of electric text processing and retrieve |
| US20080215429A1 (en) * | 2005-11-01 | 2008-09-04 | Jorey Ramer | Using a mobile communication facility for offline ad searching |
| US20090222329A1 (en) * | 2005-09-14 | 2009-09-03 | Jorey Ramer | Syndication of a behavioral profile associated with an availability condition using a monetization platform |
| CN102819612A (en) * | 2012-08-29 | 2012-12-12 | 北京鼎盾信息科技有限公司 | Full text search method based on print documents |
| CN102880617A (en) * | 2011-07-15 | 2013-01-16 | 无锡物联网产业研究院 | Internet-of-things entity searching method and system |
| CN102968669A (en) * | 2011-08-31 | 2013-03-13 | 富士通株式会社 | Method and device for predicating load |
| US20140351255A1 (en) * | 2012-08-07 | 2014-11-27 | Naver Corporation | Method and system for recommending keyword based on semantic area |
| CN104239463A (en) * | 2014-09-02 | 2014-12-24 | 百度在线网络技术（北京）有限公司 | Search method and search engine |
| US20160036751A1 (en) * | 2014-07-31 | 2016-02-04 | Samsung Electronics Co., Ltd. | Apparatus and method for providing information |
| US9406077B1 (en) * | 2011-10-19 | 2016-08-02 | Google Inc. | System and method for ad keyword scoring |
| CN106156257A (en) * | 2015-04-28 | 2016-11-23 | 北大方正集团有限公司 | A kind of Tendency Prediction method of microblogging public sentiment event |
| CN107172151A (en) * | 2017-05-18 | 2017-09-15 | 百度在线网络技术（北京）有限公司 | Method and apparatus for pushed information |
| CN107480162A (en) * | 2017-06-15 | 2017-12-15 | 北京百度网讯科技有限公司 | Searching method, device, equipment and computer-readable recording medium based on artificial intelligence |
| CN108121754A (en) * | 2016-11-30 | 2018-06-05 | 北京国双科技有限公司 | A kind of method and device for obtaining keyword attribute combination |
| CN108345686A (en) * | 2018-03-08 | 2018-07-31 | 广州赫炎大数据科技有限公司 | A kind of data analysing method and system based on search engine technique |
-
2019
- 2019-01-23 CN CN201910063092.0A patent/CN111475536B/en active Active
Patent Citations (15)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20090222329A1 (en) * | 2005-09-14 | 2009-09-03 | Jorey Ramer | Syndication of a behavioral profile associated with an availability condition using a monetization platform |
| US20080215429A1 (en) * | 2005-11-01 | 2008-09-04 | Jorey Ramer | Using a mobile communication facility for offline ad searching |
| WO2008098467A1 (en) * | 2007-02-15 | 2008-08-21 | Erzhong Liu | Convenient method and system of electric text processing and retrieve |
| CN102880617A (en) * | 2011-07-15 | 2013-01-16 | 无锡物联网产业研究院 | Internet-of-things entity searching method and system |
| CN102968669A (en) * | 2011-08-31 | 2013-03-13 | 富士通株式会社 | Method and device for predicating load |
| US9406077B1 (en) * | 2011-10-19 | 2016-08-02 | Google Inc. | System and method for ad keyword scoring |
| US20140351255A1 (en) * | 2012-08-07 | 2014-11-27 | Naver Corporation | Method and system for recommending keyword based on semantic area |
| CN102819612A (en) * | 2012-08-29 | 2012-12-12 | 北京鼎盾信息科技有限公司 | Full text search method based on print documents |
| US20160036751A1 (en) * | 2014-07-31 | 2016-02-04 | Samsung Electronics Co., Ltd. | Apparatus and method for providing information |
| CN104239463A (en) * | 2014-09-02 | 2014-12-24 | 百度在线网络技术（北京）有限公司 | Search method and search engine |
| CN106156257A (en) * | 2015-04-28 | 2016-11-23 | 北大方正集团有限公司 | A kind of Tendency Prediction method of microblogging public sentiment event |
| CN108121754A (en) * | 2016-11-30 | 2018-06-05 | 北京国双科技有限公司 | A kind of method and device for obtaining keyword attribute combination |
| CN107172151A (en) * | 2017-05-18 | 2017-09-15 | 百度在线网络技术（北京）有限公司 | Method and apparatus for pushed information |
| CN107480162A (en) * | 2017-06-15 | 2017-12-15 | 北京百度网讯科技有限公司 | Searching method, device, equipment and computer-readable recording medium based on artificial intelligence |
| CN108345686A (en) * | 2018-03-08 | 2018-07-31 | 广州赫炎大数据科技有限公司 | A kind of data analysing method and system based on search engine technique |
Non-Patent Citations (3)
| Title |
|---|
| YAQING FAN ET.AL.: "High-Frequency Keywords to Predict Defects for Android Applications", 2018 IEEE 42ND ANNUAL COMPUTER SOFTWARE AND APPLICATIONS CONFERENCE (COMPSAC) * |
| 温丽;蔡永铭;: "基于搜索引擎数据的流感监测预警", 分子影像学杂志, no. 02 * |
| 肖屹: "基于搜索引擎数据的疾病空间分布监测", 中国优秀硕士学位论文全文数据库 (信息科技辑) * |
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