System and method for scoring search results, electronic device and storage medium

Abstract

The application provides a system and method for scoring search results, an electronic device and a storage medium. The method for scoring search results comprises the following steps: obtaining search materials; scoring the same search materials based on a plurality of calculation formulas to obtain different scoring results; receiving user search information; selecting a corresponding calculation formula based on the user search information to obtain a corresponding scoring value. The method for scoring search results improves the problem that, in the prior art, an enterprise-level search process cannot complete fast and efficient positioning and query under the condition of ensuring information security.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of Internet, and in particular to a system and method for scoring search results for different users, an electronic device and a storage medium. BACKGROUND

[0002] The rapid development of the Internet industry has brought us great convenience. Reviewing the development history of the entire Internet industry, from the PC era to the mobile Internet era, from the mobile Internet era to the IOT (Internet of Things) era, and now from the IOT era to the AI (Artificial Intelligence) era, behind these rapid developments is actually a huge change in data utilization.

[0003] The speed of enterprise informatization is also increasing rapidly, and various application systems are becoming more and more perfect. While the pace of informationization construction is constantly advancing, the information resources within the enterprise are also expanding more and more seriously. Consequently, the cost of searching for information resources has doubled, and the efficiency is very low. How to complete fast and efficient positioning and query while ensuring information security has become the main problem to be solved by enterprise-level search. SUMMARY

[0004] The purpose of the present application is to provide a system and method for scoring search results for different users, an electronic device and a storage medium. The method can solve the problem of not being able to complete fast and efficient positioning and query while ensuring information security in the process of enterprise-level search in the prior art.

[0005] To achieve the above-mentioned purpose, the present application provides the following technical solutions:

[0006] The present application provides a method for scoring search results for different users, which specifically includes:

[0007] Obtaining search materials;

[0008] Scoring the same search materials based on a plurality of calculation formulas to obtain different scoring results;

[0009] Receiving user search information;

[0010] Selecting a corresponding calculation formula based on the user search information to obtain a corresponding scoring value.

[0011] Based on the above technical solutions, the present application can also be improved as follows:

[0012] Further, the scoring of the same search materials based on a plurality of calculation formulas to obtain different scoring results includes:

[0013] Multi-dimensionally dividing the search materials;

[0014] According to the big data, the search material of each dimension is scored to obtain a corresponding scoring result.

[0015] Further, the scoring of the same search material based on the plurality of calculation formulas to obtain different scoring results further comprises:

[0016] According to formula 1, the simplified material heat score is calculated;

[0017] Simplified material heat score = total historical activity / time factor formula 1;

[0018] Wherein, the total historical activity = download volume + share volume + browse volume; time factor = 1 + (current date - latest use date); if the latest use date is empty, the time factor = 1.

[0019] Further, the scoring of the same search material based on the plurality of calculation formulas to obtain different scoring results further comprises:

[0020] The scoring result is stored;

[0021] The scoring result is updated to the ES and the database at the same time.

[0022] Further, the corresponding calculation formula is selected based on the user search information to obtain a corresponding scoring value, comprising:

[0023] Obtain user information;

[0024] Based on the user information, the formula routing is selected by drools, the corresponding calculation formula is selected according to the user information of different dimensions, and the corresponding scoring value is obtained.

[0025] A system for scoring search of thousands of people and thousands of faces, comprising:

[0026] An acquisition module for acquiring search material;

[0027] A calculation module for scoring the same search material based on a plurality of calculation formulas to obtain different scoring results;

[0028] A receiving module for receiving user search information;

[0029] A selection module for selecting a corresponding calculation formula based on the user search information to obtain a corresponding scoring value.

[0030] Further, the calculation module is further used for:

[0031] Based on formula 1, the simplified material heat score is obtained;

[0032] Simplified material hotness = total historical activity / time factor Formula 1

[0033] Wherein, the total historical activity = download volume + share volume + browse volume; time factor = 1 + (current date - latest use date); if the latest use date is empty, the time factor = 1.

[0034] Further, the system for scoring the thousand faces search of the present application further comprises a storage module for storing the scoring results; and the scoring results are simultaneously updated to the ES and the database.

[0035] An electronic device comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, wherein the processor implements the steps of the method when executing the computer program.

[0036] A non-transitory computer-readable storage medium having a computer program stored thereon, wherein the computer program is executable by a processor to implement the steps of the method.

[0037] The present application has the following advantages:

[0038] The method for scoring the thousand faces search of the present application acquires search materials; scores the same search materials based on a plurality of calculation formulas to obtain different scoring results; receives user search information; selects a corresponding calculation formula based on the user search information to obtain a corresponding scoring value; maps different dimensions of search to different formulas, and different formulas point to different scores, thereby affecting the search results, and achieving the thousand faces search at the data level. BRIEF DESCRIPTION OF DRAWINGS

[0039] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings needed to be used in the embodiments or the prior art description. Obviously, the drawings in the following description are some embodiments of the present application, and those skilled in the art can obtain other drawings according to these drawings without creative labor.

[0040] Figure 1 Flowchart of the method for scoring the thousand faces search of the present application;

[0041] Figure 2 Block diagram of the system for scoring the thousand faces search of the present application;

[0042] Figure 3 Block diagram of the system for scoring the thousand faces search of the present application;

[0043] Figure 4 An electronic device entity structure schematic diagram provided by the present application.

[0044] Reference signs

[0045] The acquisition module 10, the calculation module 20, the receiving module 30, the selection module 40, the storage module 50, the electronic device 60, the processor 601, the memory 602, and the bus 603. DETAILED DESCRIPTION

[0046] To make the objects, technical solutions, and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be described below in a clear and complete manner with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are some but not all of the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by a person of ordinary skill in the art without creative work fall within the protection scope of the present application.

[0047] The technical solutions of the present application will be described in detail below with specific embodiments. The following specific embodiments can be combined with each other, and some embodiments can not be described again for the same or similar concepts or processes.

[0048] Figure 1 A flowchart of a method for scoring a thousand faces search according to an embodiment of the present application is shown in FIG. 1. The method for scoring a thousand faces search according to an embodiment of the present application includes the following steps: Figure 1

[0049] S101, acquiring search materials;

[0050] Specifically, a thousand faces search is a search rule. The same words are searched, and the products seen on different people's mobile phones are different, which is also called "a thousand faces". A thousand faces should be said to be one of the most important changes now and in the future. The algorithm system will actively push things it thinks suitable for you according to your historical records and search requests.

[0051] The search materials for which a scoring result is desired are acquired.

[0052] S102, scoring the same search materials based on a plurality of calculation formulas to obtain different scoring results;

[0053] Specifically, the search materials are divided in multiple dimensions.

[0054] The search materials in each dimension are scored according to big data to obtain corresponding scoring results.

[0055] The hotness score of the simplified materials is calculated according to Formula 1. ​

[0056] Simplify material hotness score = history total active / time factor formula 1;

[0057] Wherein, the history total active = download volume + share volume + browse volume; time factor = 1 + (current date - latest use date); if the latest use date is empty, the time factor = 1.

[0058] The scoring results are stored;

[0059] The scoring results are updated to ES and the database at the same time.

[0060] ES, namely, elasticsearch, provides a distributed multi-user capable full-text search engine. The index of ES is the logical storage of the logical data of ES, and the structure of the index is prepared for fast and effective full-text indexing, which does not store the original value, and the retrieved data is output in the form of json.

[0061] Big data, or massive data, refers to the data volume involved, which is so large that it cannot be captured, managed, processed and arranged into information to help enterprise decision-making more actively within a reasonable time through mainstream software tools.

[0062] In the book "Big Data Era" written by Victor Mayer-Schonberger and Kenneth Cukier, big data refers to the analysis and processing of all data instead of using shortcuts such as random analysis (sample survey). The 5V characteristics of big data (proposed by IBM): Volume (large amount), Velocity (high speed), Variety (variety), Value (low value density), Veracity (truthfulness).

[0063] Volume: The size of the data determines the value and potential information of the data considered; Variety: the diversity of data types; Velocity: refers to the speed of obtaining data; Variability: the process that hinders processing and effective management of data. Veracity: the quality of data. Complexity: the amount of data is huge, and the sources are multiple channels. Value: reasonable use of big data to create high value at low cost.

[0064] Different dimensions of the same material are calculated, and due to the huge amount of calculation, they are given to big data for calculation. At the same time, a data query interface is exposed to query the score. This score is used to affect the weight of different dimension search.

[0065] When calculating the numerical value, keep the decimal;

[0066] Currently a set of conditions corresponds to a set of formulas (multiple formulas), so there will be multiple score values

[0067] Because the score calculation is huge, the real-time data is T+1, so the data can be cached to the business system, and the corresponding time of the system is provided. Here it needs to be put into ES and database at the same time.

[0068] S103, receiving user search information;

[0069] S104, selecting the corresponding calculation formula based on the user search information to obtain the corresponding score value;

[0070] Specifically, user information is obtained;

[0071] Based on the user information, formula routing is performed through drools, and different dimensions of user information are selected to obtain the corresponding score value.

[0072] Based on user information routing to different formula scores, ABtest (comparison test) is realized. Based on different user information dimensions, such as user id role and other dimensions, drools is used for formula routing. Different scores are obtained, and thousands of people are realized.

[0073] ABTest, simply speaking, is to develop two schemes (such as two pages, one with a red button and the other with a blue button) for the same product target, let a part of users use A scheme, and another part of users use B scheme, then record the use of users through logs, and analyze related indicators such as click rate and conversion rate through structured log data, so as to obtain the scheme that meets the expected design target, and finally switch all traffic to the scheme that meets the target;

[0074] Drools (JBoss Rules) has an open source business rule engine with easy access to enterprise strategies, easy adjustment and easy management, which meets industry standards, is fast and efficient. Business analysts or auditors can easily view business rules using it, so as to verify whether the rules executed have the required business rules.

[0075] The predecessor of JBossRules is an open source project called Drools of Codehaus. Recently, it has been incorporated into JBoss, renamed as JBoss Rules, and become the rule engine of JBoss application server. Drools is a rule engine based on Charles Forgy's RETE algorithm customized for Java. With OO interface of RETE, business rules have a more natural expression.

[0076] Drools' use of XML <conditons> 、 <consequence>Nodes express If--Then sentences, and inside them can be embedded code in the above languages as the condition and action.

[0077] The smartness of Drools is that it uses XML nodes to specify the definition of If--Then sentences and facts, making the engine comfortable to work.

[0078] The method for the thousand faces search scoring in the application, obtains search materials; scores the same search materials based on several calculation formulas, obtains different scoring results; receives user search information; selects corresponding calculation formula based on the user search information, obtains corresponding scoring value; maps different dimensions of search to different formulas, different formulas will point to different scores, thereby affecting the search result, and the thousand faces search is achieved at the data level.

[0079] Figures 2-3 The flow chart of the system embodiment of the thousand faces search scoring in the application; as shown in the figure, Figures 2-3 The system for the thousand faces search scoring provided by the embodiment of the application comprises the following steps:

[0080] The obtaining module 10 is used for obtaining search materials;

[0081] The calculation module 20 is used for scoring the same search materials based on several calculation formulas, and obtaining different scoring results; and the simplified material heat score is obtained based on formula 1.

[0082] Simplified material heat score = history total activity / time factor formula 1.

[0083] The history total activity = download amount + sharing amount + browsing amount; the time factor = 1 + (current date - latest use date); if the latest use date is empty, the time factor = 1.

[0084] The receiving module 30 is used for receiving user search information;

[0085] The selection module 40 is used for selecting corresponding calculation formula based on the user search information, and obtaining corresponding scoring value.

[0086] The system for scoring the thousand faces search also includes a storage module 50 that stores the scoring results; and updates the scoring results to the ES and the database.

[0087] The system for scoring the thousand faces search in the application obtains search materials through the obtaining module 10; scores the same search materials based on several calculation formulas through the calculation module 20 to obtain different scoring results; stores the scoring results through the storage module 50, and updates the scoring results to the ES and the database; receives user search information through the receiving module 30; selects corresponding calculation formulas based on the user search information through the selection module 40 to obtain corresponding scoring values; maps different dimensions of search to different formulas, different formulas point to different scores, and thus affect the search results, and the thousand faces search is achieved at the data level. The problem that the enterprise-level search process in the prior art cannot complete fast and efficient positioning and query under the condition of ensuring information security is solved.

[0088] Figure 4 An electronic device entity structure schematic diagram provided for the embodiment of the application is shown in the figure. Figure 4 As shown in the figure, the electronic device 60 includes a processor 601, a memory 602 and a bus 603.

[0089] The processor 601 and the memory 602 complete mutual communication through the bus 603.

[0090] The processor 601 is used to call program instructions in the memory 602 to execute the method provided by each method embodiment, for example, including: obtaining search materials; scoring the same search materials based on several calculation formulas to obtain different scoring results; receiving user search information; selecting corresponding calculation formulas based on the user search information to obtain corresponding scoring values.

[0091] The embodiment provides a non-transitory computer readable storage medium that stores computer instructions, and the computer instructions make the computer execute the method provided by each method embodiment, for example, including: obtaining search materials; scoring the same search materials based on several calculation formulas to obtain different scoring results; receiving user search information; selecting corresponding calculation formulas based on the user search information to obtain corresponding scoring values.

[0092] Those skilled in the art can understand that all or part of the steps of the above-mentioned method embodiments can be completed by program instruction related hardware, and the foregoing program can be stored in a computer readable storage medium, and the program performs the steps of the above-mentioned method embodiments when executed; and the foregoing storage medium includes ROM, RAM, magnetic disk or optical disk and various storage media that can store program codes.

[0093] The device embodiments described above are merely illustrative, wherein the units illustrated as separate components can or can not be physically separated, and the components illustrated as units can or can not be physical units, that is, can be located in one place, or can be distributed to multiple network units. Part or all of the modules can be selected to achieve the purpose of the embodiment scheme according to actual needs. Those skilled in the art can understand and implement without creative labor.

[0094] Through the description of the above embodiments, those skilled in the art can clearly understand that each embodiment can be realized by means of software and necessary general hardware platform, and of course can also be realized by hardware. Based on such understanding, the above technical solutions can be embodied in the form of software product, which can be stored in a computer readable storage medium, such as ROM / RAM, magnetic disk or optical disk, and includes a plurality of instructions to make a computer device (which can be a personal computer, server or network device) execute the method of each embodiment or some part of the embodiment.

[0095] Finally, it should be noted that: the above embodiments are only used to illustrate the technical solutions of the present application, and not to limit them; although the present application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that they can still modify the technical solutions recorded in the foregoing embodiments, or make equivalent replacement for some technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present application.

[0096] The above only describes the preferred embodiments of the present application and is not intended to limit the present application. For those skilled in the art, the present application can have various modifications and changes. Any modification, equivalent replacement, improvement, etc. made within the spirit and principles of the present application shall be included in the protection scope of the present application.< / consequence> < / conditons>

Claims

1. A method for scoring personalized search, characterized in that, The method is applied to an enterprise information system to realize positioning and query of internal information resources of the enterprise, and specifically comprises the following steps: Obtaining search materials; Scoring the same search materials based on a plurality of calculation formulas to obtain different scoring results; Multi-dimensionally dividing the search materials; scoring the search materials of each dimension based on big data to obtain corresponding scoring results; Calculating a simplified material heat score according to formula 1; the simplified material heat score = total historical activity / time factor formula 1; wherein the total historical activity = download volume + share volume + browse volume; the time factor = 1 + (current date - latest use date); if the latest use date is empty, the time factor = 1; Storing the scoring results; and updating the scoring results to an ES and a database at the same time; Receiving user search information; Obtaining user information; selecting a formula route based on the user information through drools; selecting a corresponding calculation formula according to user information of different dimensions to obtain a corresponding scoring value.

2. A system for scoring personalized search, characterized in that, The method is applied to an enterprise information system to realize positioning and query of internal information resources of the enterprise, and specifically comprises the following steps: An obtaining module for obtaining search materials; A calculation module for scoring the same search materials based on a plurality of calculation formulas to obtain different scoring results; Multi-dimensionally dividing the search materials; scoring the search materials of each dimension based on big data to obtain corresponding scoring results; Obtaining a simplified material heat score based on formula 1; A storage module for storing the scoring results; and updating the scoring results to an ES and a database at the same time; A receiving module for receiving user search information; A selection module for obtaining user information; selecting a formula route based on the user information through drools; selecting a corresponding calculation formula according to user information of different dimensions to obtain a corresponding scoring value.

3. An electronic device comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, characterized in that, The processor executes the computer program to realize the steps of the method of claim 1.

4. A non-transitory computer-readable storage medium having stored thereon a computer program, characterized in that, The computer program is executed by the processor to realize the steps of the method of claim 1.

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