Information retrieval method and related device, medium and program product

Abstract

The present application relates to the field of big data technology, and in particular to an information retrieval method and related devices, media, and program products, the method comprising: obtaining a target keyword set, the target keyword set including at least one keyword; determining a target complexity corresponding to the target keyword set; determining a target retrieval control parameter corresponding to the target complexity; performing a search according to the target retrieval control parameter to obtain a target retrieval result. The use of the embodiments of the present application can improve information retrieval efficiency.

Description

Technical Field

[0001] The present application relates to the field of big data and data processing technology, and specifically to information retrieval methods and related devices, media and program products. Background Art

[0002] Information retrieval is the main way for users to query and obtain information. It is a method and means of finding information. That is, users use certain methods and retrieval tools to find the required information from the information collection according to their needs. How to improve the efficiency of information retrieval needs to be solved urgently. Summary of the invention

[0003] The embodiments of the present application provide an information retrieval method and related devices, media and program products, which can improve information retrieval efficiency.

[0004] In a first aspect, an embodiment of the present application provides an information retrieval method, the method comprising:

[0005] Acquire a target keyword set, wherein the target keyword set includes at least one keyword;

[0006] Determining a target complexity corresponding to the target keyword set;

[0007] Determining a target retrieval control parameter corresponding to the target complexity;

[0008] A search is performed according to the target search control parameters to obtain a target search result.

[0009] In a second aspect, an embodiment of the present application provides an information retrieval device, the device comprising: an acquisition unit, a first determination unit, a second determination unit and a retrieval unit, wherein:

[0010] The acquisition unit is used to acquire a target keyword set, wherein the target keyword set includes at least one keyword;

[0011] The first determining unit is used to determine the target complexity corresponding to the target keyword set;

[0012] The second determining unit is used to determine the target retrieval control parameter corresponding to the target complexity;

[0013] The retrieval unit is used to perform retrieval according to the target retrieval control parameter to obtain a target retrieval result.

[0014] In a third aspect, an embodiment of the present application provides an electronic device, comprising a processor, a memory, a communication interface, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the processor, and the program includes instructions for executing the steps in the first aspect of the embodiment of the present application.

[0015] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program for electronic data exchange, wherein the computer program enables a computer to execute part or all of the steps described in the first aspect of the embodiment of the present application.

[0016] In a fifth aspect, an embodiment of the present application provides a computer program product, wherein the computer program product includes a non-transitory computer-readable storage medium storing a computer program, and the computer program is operable to cause a computer to execute some or all of the steps described in the first aspect of the embodiment of the present application. The computer program product may be a software installation package.

[0017] The implementation of the embodiments of the present application has the following beneficial effects:

[0018] It can be seen that the information retrieval method, electronic device and related products described in the embodiments of the present application obtain a target keyword set, the target keyword set includes at least one keyword, determines the target complexity corresponding to the target keyword set, determines the target retrieval control parameters corresponding to the target complexity, performs retrieval according to the target retrieval control parameters, and obtains the target retrieval results. Furthermore, it is possible to decide on the corresponding retrieval control algorithm based on the complexity of the keywords, which helps to improve the retrieval efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0020] Figure 1 It is a flowchart of an information retrieval method provided in an embodiment of the present application;

[0021] Figure 2 It is a flowchart of another information retrieval method provided in an embodiment of the present application;

[0022] Figure 3 It is a structural schematic diagram of an electronic device provided in an embodiment of the present application;

[0023] Figure 4 It is a block diagram of the functional units of an information retrieval device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0024] The terms "first", "second", etc. in the specification and claims of this application and the above-mentioned drawings are used to distinguish different objects, rather than to describe a specific order. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not limited to the listed steps or units, but in a possible example also includes steps or units that are not listed, or in a possible example also includes other steps or units inherent to these processes, methods, products or devices.

[0025] Reference to "embodiments" herein means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present application. The appearance of the phrase in various locations in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0026] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0027] The electronic devices involved in the embodiments of the present application may include but are not limited to: smart phones, tablet computers, intelligent robots, vehicle-mounted devices, wearable devices, computing devices or other processing devices connected to wireless modems, as well as various forms of user equipment (UE), mobile stations (MS), terminal devices, etc., without limitation here, and the electronic device may also be a server.

[0028] See also Figure 1 , Figure 1 : is a flow chart of an information retrieval method provided by an embodiment of the present application. As shown in the figure, it is applied to an electronic device. The information retrieval method includes:

[0029] A target keyword set is obtained, wherein the target keyword set includes at least one keyword. In the embodiment of the present application, the target keyword set may include at least one keyword, and the keyword may be at least one of the following: text, icon, character string, punctuation mark, calculation formula, etc., which are not limited here. The embodiment of the present application can be applied to various systems that require retrieval, such as patent retrieval systems, web page search systems, company internal search systems, etc., which are not limited here.

[0030] In a specific implementation, the target keyword set may be input by a user. For example, the target keyword set may exist in an Excel table. When the Excel table is loaded, the target keyword set may be automatically obtained. For another example, the target keyword set may exist in at least one image. Keyword extraction may be performed on the at least one image, and the extracted keywords are used as the target keyword set. For another example, the target keyword set may exist in a video. Keyword extraction may be performed on the video, and the extracted keywords are used as the target keyword set. For another example, the target keyword set may exist in a speech. Keyword extraction may be performed on the speech, and the extracted keywords are used as the target keyword set.

[0031] Optionally, the above step 101, obtaining the target keyword set, may include the following steps:

[0032] 11. Obtain the target image;

[0033] 12. Perform character recognition on the target image to obtain a target text;

[0034] 13. Perform keyword extraction on the target text to obtain x first keywords, where x is an integer greater than 1;

[0035] 14. Perform icon recognition on the target image to obtain Q icons, where Q is a natural number;

[0036] 15. Determine the keyword corresponding to each of the Q icons according to the preset mapping relationship between icons and keywords, and obtain y second keywords;

[0037] 16. Use the x first keywords and the y second keywords as the target keyword set.

[0038] The target image may be one image or multiple images, and the target image may be a screenshot or a pre-stored picture. The electronic device may pre-store a mapping relationship between preset icons and keywords. In a specific implementation, the electronic device may obtain the target image, and may also perform character recognition on the target image to obtain a target text, and then may perform keyword extraction on the target text to obtain x first keywords, where x is an integer greater than 1. In addition, the target image may also perform icon recognition to obtain Q icons, where Q is a natural number, and then determine the keyword corresponding to each of the Q icons according to the mapping relationship between the preset icons and keywords to obtain y second keywords, and then use the x first keywords and the y second keywords as the target keyword set. In this way, keywords can be quickly obtained through character recognition or icon recognition.

[0039] 102. Determine a target complexity corresponding to the target keyword set.

[0040] In the specific implementation, different complexities require different retrieval algorithms. The retrieval algorithm can be at least one of the following: vector space model, probability retrieval model, language model, Boolean model, reasoning network, extended Boolean retrieval algorithm, latent semantic indexing algorithm, neural network algorithm, genetic algorithm, fuzzy set algorithm, etc., which are not limited here.

[0041] Optionally, the above step 102, determining the target complexity corresponding to the target keyword set, may include the following steps:

[0042] 21. Classify the keywords in the target keyword set to obtain P categories of keywords, where P is a positive integer;

[0043] 22. According to the preset mapping relationship between the category and the complexity evaluation value, determine the complexity evaluation value corresponding to each category of the P categories of keywords, and obtain P complexity evaluation values;

[0044] 23. Determine the number of keywords in the target keyword set;

[0045] 24. Determine the quantity ratio of each type of keywords in the P types of keywords according to the quantity of the keywords and the P types of keywords, and obtain P quantity ratios;

[0046] 25. Determine the target complexity according to the P complexity evaluation values ​​and the P quantity proportions.

[0047] In a specific implementation, the electronic device may pre-store a mapping relationship between a preset category and a complexity evaluation value. Specifically, the electronic device may classify the keywords in the target keyword set to obtain P categories of keywords, where P is a positive integer, and then, according to the mapping relationship between the preset category and the complexity evaluation value, the complexity evaluation value corresponding to each category of keywords in the P categories of keywords may be determined to obtain P complexity evaluation values. The number of keywords in the target keyword set may also be determined, and the number proportion of each category of keywords in the P categories of keywords may be determined according to the number of keywords and the P categories of keywords to obtain P number proportions. The target complexity may be determined according to the P complexity evaluation values ​​and the P number proportions. Specifically, the target complexity may be obtained by performing a weighted operation on the P complexity evaluation values ​​and the P number proportions.

[0048] 103. Determine a target retrieval control parameter corresponding to the target complexity.

[0049] In the embodiment of the present application, the search control parameters are used to control the speed and accuracy of the search algorithm. Different complexities may correspond to different complexity levels, and different complexity levels may correspond to different search control parameters.

[0050] Optionally, the above step 103, determining the target retrieval control parameter corresponding to the target complexity, may include the following steps:

[0051] 31. Determine the target algorithm type identifier corresponding to the target complexity according to the mapping relationship between the preset complexity and the algorithm type identifier;

[0052] 32. Obtain corresponding reference algorithm control parameters according to the target algorithm type identifier;

[0053] 33. Determine the popularity value corresponding to each keyword in the target keyword set to obtain multiple popularity values;

[0054] 34. Determine a heat average according to the multiple heat values;

[0055] 35. Determine the popularity value corresponding to each keyword in the P keywords to obtain P popularity values;

[0056] 36. Determine a target mean square error according to the P heat values;

[0057] 37. Determine the target optimization coefficient corresponding to the target mean square error according to the preset mapping relationship between the mean square error and the optimization coefficient;

[0058] 38. Optimize the heat mean according to the target optimization coefficient to obtain a reference heat mean;

[0059] 39. Determine the target adjustment coefficient corresponding to the reference heat average value according to the preset mapping relationship between the heat average value and the adjustment coefficient;

[0060] 40. Adjust the reference algorithm control parameter according to the target adjustment coefficient to obtain the target algorithm control parameter;

[0061] 41. Use the target algorithm type identifier and the target algorithm control parameter as the target retrieval control parameter.

[0062] In a specific implementation, the electronic device may pre-store a mapping relationship between a preset complexity and an algorithm type identifier, and different algorithm type identifiers may correspond to different algorithms. The electronic device may also pre-store a mapping relationship between a preset mean square error and an optimization coefficient, as well as a preset heat mean and an adjustment coefficient.

[0063] Specifically, the electronic device can determine the target algorithm type identifier corresponding to the target complexity according to the mapping relationship between the preset complexity and the algorithm type identifier, and then obtain the corresponding reference algorithm control parameters according to the target algorithm type identifier.

[0064] Furthermore, the electronic device may determine the popularity value corresponding to each keyword in the target keyword set, and obtain multiple popularity values. Different keywords may correspond to different popularity, and popularity may be understood as the number of times or frequency that the keyword is searched. The electronic device can also determine the heat mean value based on multiple heat values, and determine the heat value corresponding to each type of keyword in P types of keywords to obtain P heat values, and then determine the target mean square error based on the P heat values, and then determine the target optimization coefficient corresponding to the target mean square error according to the preset mapping relationship between the mean square error and the optimization coefficient. Since different keywords in the keyword set themselves have a certain correlation, and the mean square error can reflect the fluctuation between the keywords, the heat mean value is optimized according to the target optimization coefficient to obtain a reference heat mean value, and then determine the target adjustment coefficient corresponding to the reference heat mean value according to the preset mapping relationship between the heat mean value and the adjustment coefficient. Then, one or more parameters of the reference algorithm control parameters can be adjusted according to the target adjustment coefficient to obtain the target algorithm control parameters. Finally, the target algorithm type identifier and the target algorithm control parameters are used as target retrieval control parameters. In this way, the control parameters of the retrieval algorithm control algorithm can be adjusted according to the characteristics between the keywords to obtain retrieval control parameters that are more suitable for the keyword set, which helps to improve the retrieval accuracy or efficiency.

[0065] 104. Perform a search according to the target search control parameter to obtain a target search result.

[0066] In a specific implementation, the electronic device can perform a search through target retrieval control parameters, and thus, can obtain target retrieval results, and can also display the target retrieval results. For example, the retrieval results can be displayed in chronological order, or for another example, the retrieval results can be displayed in order from high to low relevance.

[0067] Optionally, the above step 104, performing a search according to the target search control parameter to obtain a target search result, may include the following steps:

[0068] A41. Obtain the target identity level of the user;

[0069] A42. Determine the target database identifier corresponding to the target identity level according to the preset mapping relationship between the identity level and the database identifier;

[0070] A43. Search the database corresponding to the target database identifier according to the target search control parameter to obtain the target search result.

[0071] In the embodiment of the present application, different user identities may correspond to different identity levels, and the electronic device may pre-store a mapping relationship between a preset identity level and a database identifier.

[0072] Specifically, the electronic device can obtain the user's target identity level, determine the target database identifier corresponding to the target identity level according to the mapping relationship between the preset identity level and the database identifier, and can also search the database corresponding to the target database identifier according to the target retrieval control parameters to obtain the target retrieval results, that is, it can determine the corresponding database based on the user's identity, and then search the database. For example, members and non-members can correspond to different databases, and the database corresponding to members can be richer than the database for non-members.

[0073] Optionally, the above step 104, performing a search according to the target search control parameter to obtain a target search result, may include the following steps:

[0074] B41, grouping the target keyword set to obtain a plurality of first groups;

[0075] B42, deriving and expanding each of the multiple groups to obtain multiple second groups;

[0076] B43, configuring a process for each of the plurality of second groups to obtain a plurality of processes;

[0077] B44, performing a search according to the multiple processes, the multiple second groups, and the target search control parameter to obtain multiple search result sets;

[0078] B45, determining the number of intersections between each search result in the plurality of search result sets and other search results, to obtain a plurality of intersection numbers;

[0079] B46, performing deduplication processing on the multiple search result sets to obtain multiple search results;

[0080] B47. According to the principle of multi-priority sorting based on the number of intersections, the multiple search results are sorted according to the multiple numbers of intersections, and the top X search results are used as the target search results, where X is an integer greater than 1.

[0081] In a specific implementation, the electronic device can group the target keyword set to obtain multiple first groups, and can also derive and expand each of the multiple groups to obtain multiple second groups. For example, the synonyms, antonyms, network terms, and synonyms of a word in other national languages ​​can be derived and expanded. A process can also be configured for each of the multiple second groups to obtain multiple processes, and then searches can be performed according to the multiple processes, multiple second groups, and target search control parameters to obtain multiple search result sets, that is, each second group can correspond to a search result set.

[0082] Furthermore, the electronic device can also determine the number of intersections in which each search result in multiple search result sets intersects with other search results, obtain multiple intersection numbers, and then deduplicate the multiple search result sets to obtain multiple search results, and sort the multiple search results according to the multiple intersection numbers according to the principle of multi-priority sorting based on the number of intersections, and use the top X search results as target search results, where X is an integer greater than 1. First, grouping and expanding keywords can enrich keywords to retrieve more relevant information; second, using multiple processes can allow multiple processes to search in parallel, which can improve search efficiency; third, the display order of search results can be determined based on the intersection attributes between different sets, and then, search results with strong correlation can be displayed first, which helps to improve search efficiency.

[0083] It can be seen that the information retrieval method described in the embodiment of the present application obtains a target keyword set, the target keyword set includes at least one keyword, determines the target complexity corresponding to the target keyword set, determines the target retrieval control parameters corresponding to the target complexity, performs retrieval according to the target retrieval control parameters, and obtains the target retrieval results. Furthermore, the corresponding retrieval control algorithm can be decided based on the complexity of the keywords, which helps to improve the retrieval efficiency.

[0084] With the above Figure 1 For the embodiments shown, please refer to Figure 2 , Figure 2: is a flowchart of an information retrieval method provided in an embodiment of the present application, which is applied to an electronic device. The information retrieval method includes:

[0085] 201. Obtain a target keyword set, where the target keyword set includes at least one key.

[0086] 202. Determine whether the number of keywords in the target keyword set is greater than a preset number.

[0087] The preset number can be set by the user or by system default.

[0088] 203. When the number of keywords in the target keyword set is greater than the preset number, detect whether the number of keyword categories included in the target keyword set is greater than the preset number of categories.

[0089] The preset number of categories can be set by the user or by the system. Of course, the electronic device can directly use the default search algorithm and perform a search operation based on the target keyword set when determining that the number of keywords in the target keyword set is less than or equal to the preset number.

[0090] 204. When the number of keyword categories included in the target keyword set is greater than the preset number of categories, determine a target complexity corresponding to the target keyword set.

[0091] When the number of keyword categories included in the target keyword set is less than or equal to the preset number of categories, the electronic device may directly adopt a default search algorithm and perform a search operation according to the target keyword set.

[0092] 205. Determine a target retrieval control parameter corresponding to the target complexity.

[0093] 206. Perform a search according to the target search control parameter to obtain a target search result.

[0094] The specific description of the above steps 201, 204 to 206 can refer to the above Figure 1 The corresponding steps of the described information retrieval method will not be repeated here.

[0095] It can be seen that the information retrieval method described in the embodiment of the present application obtains a target keyword set, the target keyword set includes at least one keyword, determines whether the number of keywords in the target keyword set is greater than a preset number, and when the number of keywords in the target keyword set is greater than the preset number, detects whether the number of keyword categories included in the target keyword set is greater than the preset number of categories, and when the number of keyword categories included in the target keyword set is greater than the preset number of categories, determines the target complexity corresponding to the target keyword set, determines the target retrieval control parameters corresponding to the target complexity, performs retrieval according to the target retrieval control parameters, and obtains the target retrieval results. Furthermore, the corresponding retrieval control algorithm can be decided based on the complexity of the keywords, which helps to improve the retrieval efficiency.

[0096] In accordance with the above embodiment, please refer to Figure 3 , Figure 3 1 is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application. As shown in the figure, the electronic device includes a processor, a memory, a communication interface, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the processor. In the embodiment of the present application, the program includes instructions for executing the following steps:

[0097] Acquire a target keyword set, wherein the target keyword set includes at least one keyword;

[0098] Determining a target complexity corresponding to the target keyword set;

[0099] Determining a target retrieval control parameter corresponding to the target complexity;

[0100] A search is performed according to the target search control parameters to obtain a target search result.

[0101] It can be seen that the electronic device described in the embodiment of the present application obtains a target keyword set, the target keyword set includes at least one keyword, determines the target complexity corresponding to the target keyword set, determines the target retrieval control parameters corresponding to the target complexity, performs a search according to the target retrieval control parameters, and obtains a target retrieval result. Furthermore, it can decide on a corresponding retrieval control algorithm based on the complexity of the keyword, which helps to improve retrieval efficiency.

[0102] Optionally, in determining the target complexity corresponding to the target keyword set, the program includes instructions for executing the following steps:

[0103] Classify the keywords in the target keyword set to obtain P categories of keywords, where P is a positive integer;

[0104] According to the preset mapping relationship between the category and the complexity evaluation value, determine the complexity evaluation value corresponding to each category of the P categories of keywords, and obtain P complexity evaluation values;

[0105] determining the number of keywords in the target keyword set;

[0106] Determine the quantity ratio of each type of keywords in the P types of keywords according to the quantity of keywords and the P types of keywords, and obtain P quantity ratios;

[0107] The target complexity is determined according to the P complexity evaluation values ​​and the P quantity proportions.

[0108] Optionally, in determining the target retrieval control parameter corresponding to the target complexity, the program includes instructions for executing the following steps:

[0109] Determine the target algorithm type identifier corresponding to the target complexity according to the mapping relationship between the preset complexity and the algorithm type identifier;

[0110] Acquire corresponding reference algorithm control parameters according to the target algorithm type identifier;

[0111] Determine the popularity value corresponding to each keyword in the target keyword set to obtain multiple popularity values;

[0112] Determine a heat average value according to the multiple heat values;

[0113] Determine the popularity value corresponding to each keyword in the P categories of keywords to obtain P popularity values;

[0114] Determine a target mean square error according to the P heat values;

[0115] According to a preset mapping relationship between the mean square error and the optimization coefficient, a target optimization coefficient corresponding to the target mean square error is determined;

[0116] Optimizing the heat mean according to the target optimization coefficient to obtain a reference heat mean;

[0117] According to the preset mapping relationship between the heat average and the adjustment coefficient, determine the target adjustment coefficient corresponding to the reference heat average;

[0118] Adjusting the reference algorithm control parameter according to the target adjustment coefficient to obtain the target algorithm control parameter;

[0119] The target algorithm type identifier and the target algorithm control parameter are used as the target retrieval control parameter.

[0120] Optionally, in the aspect of obtaining the target keyword set, the program includes instructions for executing the following steps:

[0121] Get the target image;

[0122] Performing character recognition on the target image to obtain a target text;

[0123] Perform keyword extraction on the target text to obtain x first keywords, where x is an integer greater than 1;

[0124] Performing icon recognition on the target image to obtain Q icons, where Q is a natural number;

[0125] According to a preset mapping relationship between icons and keywords, determine the keyword corresponding to each of the Q icons to obtain y second keywords;

[0126] The x first keywords and the y second keywords are used as the target keyword set.

[0127] Optionally, in the aspect of performing a search according to the target search control parameter to obtain a target search result, the program includes instructions for executing the following steps:

[0128] Get the user's target identity level;

[0129] Determine the target database identifier corresponding to the target identity level according to the preset mapping relationship between the identity level and the database identifier;

[0130] The database corresponding to the target database identifier is searched according to the target search control parameter to obtain the target search result.

[0131] The above mainly introduces the scheme of the embodiment of the present application from the perspective of the execution process on the method side. It is understandable that, in order to realize the above functions, it includes hardware structures and / or software modules corresponding to the execution of each function. Those skilled in the art should be easily aware that, in combination with the units and algorithm steps of each example described in the embodiment provided herein, the present application can be implemented in the form of hardware or a combination of hardware and computer software. Whether a function is executed in the form of hardware or computer software driving hardware depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of the present application.

[0132] The embodiment of the present application can divide the functional units according to the above method example. For example, each functional unit can be divided according to each function, or two or more functions can be integrated into one processing unit. The above integrated unit can be implemented in the form of hardware or in the form of software functional units. It should be noted that the division of units in the embodiment of the present application is schematic and is only a logical function division. There may be other division methods in actual implementation.

[0133] Figure 4 4 is a functional unit composition block diagram of an information retrieval device 400 involved in an embodiment of the present application. The device 400 includes: an acquisition unit 401, a first determination unit 402, a second determination unit 403 and a retrieval unit 404, wherein:

[0134] The acquisition unit 401 is used to acquire a target keyword set, wherein the target keyword set includes at least one keyword;

[0135] The first determining unit 402 is used to determine the target complexity corresponding to the target keyword set;

[0136] The second determining unit 403 is used to determine the target retrieval control parameter corresponding to the target complexity;

[0137] The retrieval unit 404 is used to perform retrieval according to the target retrieval control parameter to obtain a target retrieval result.

[0138] It can be seen that the information retrieval device described in the embodiment of the present application obtains a target keyword set, the target keyword set includes at least one keyword, determines the target complexity corresponding to the target keyword set, determines the target retrieval control parameters corresponding to the target complexity, performs retrieval according to the target retrieval control parameters, and obtains the target retrieval results. Furthermore, it can decide on the corresponding retrieval control algorithm based on the complexity of the keywords, which helps to improve the retrieval efficiency.

[0139] Optionally, in determining the target complexity corresponding to the target keyword set, the first determining unit 402 is specifically configured to:

[0140] Classify the keywords in the target keyword set to obtain P categories of keywords, where P is a positive integer;

[0141] According to the preset mapping relationship between the category and the complexity evaluation value, determine the complexity evaluation value corresponding to each category of the P categories of keywords, and obtain P complexity evaluation values;

[0142] determining the number of keywords in the target keyword set;

[0143] Determine the quantity ratio of each type of keywords in the P types of keywords according to the quantity of keywords and the P types of keywords, and obtain P quantity ratios;

[0144] The target complexity is determined according to the P complexity evaluation values ​​and the P quantity proportions.

[0145] Optionally, in determining the target retrieval control parameter corresponding to the target complexity, the second determining unit 403 is specifically configured to:

[0146] Determine the target algorithm type identifier corresponding to the target complexity according to the mapping relationship between the preset complexity and the algorithm type identifier;

[0147] Acquire corresponding reference algorithm control parameters according to the target algorithm type identifier;

[0148] Determine the popularity value corresponding to each keyword in the target keyword set to obtain multiple popularity values;

[0149] Determine a heat average value according to the multiple heat values;

[0150] Determine the popularity value corresponding to each keyword in the P categories of keywords to obtain P popularity values;

[0151] Determine a target mean square error according to the P heat values;

[0152] According to a preset mapping relationship between the mean square error and the optimization coefficient, a target optimization coefficient corresponding to the target mean square error is determined;

[0153] Optimizing the heat mean according to the target optimization coefficient to obtain a reference heat mean;

[0154] According to the preset mapping relationship between the heat average and the adjustment coefficient, determine the target adjustment coefficient corresponding to the reference heat average;

[0155] Adjusting the reference algorithm control parameter according to the target adjustment coefficient to obtain the target algorithm control parameter;

[0156] The target algorithm type identifier and the target algorithm control parameter are used as the target retrieval control parameter.

[0157] Optionally, in the aspect of acquiring the target keyword set, the acquiring unit 401 is specifically used for:

[0158] Get the target image;

[0159] Performing character recognition on the target image to obtain a target text;

[0160] Perform keyword extraction on the target text to obtain x first keywords, where x is an integer greater than 1;

[0161] Performing icon recognition on the target image to obtain Q icons, where Q is a natural number;

[0162] According to a preset mapping relationship between icons and keywords, determine the keyword corresponding to each of the Q icons to obtain y second keywords;

[0163] The x first keywords and the y second keywords are used as the target keyword set.

[0164] Optionally, in the aspect of performing the search according to the target search control parameter to obtain the target search result, the search unit 404 is specifically used to:

[0165] Get the user's target identity level;

[0166] Determine the target database identifier corresponding to the target identity level according to the preset mapping relationship between the identity level and the database identifier;

[0167] The database corresponding to the target database identifier is searched according to the target search control parameter to obtain the target search result.

[0168] It can be understood that the functions of each program module of the information retrieval device of this embodiment can be specifically implemented according to the method in the above method embodiment. The specific implementation process can refer to the relevant description of the above method embodiment, which will not be repeated here.

[0169] An embodiment of the present application also provides a computer storage medium, wherein the computer storage medium stores a computer program for electronic data exchange, wherein the computer program enables a computer to execute part or all of the steps of any method described in the above method embodiments, and the above computer includes an electronic device.

[0170] The embodiment of the present application also provides a computer program product, the computer program product includes a non-transitory computer-readable storage medium storing a computer program, the computer program is operable to cause a computer to execute some or all of the steps of any method described in the method embodiment. The computer program product may be a software installation package, and the computer includes an electronic device.

[0171] It should be noted that, for the aforementioned method embodiments, for the sake of simplicity, they are all expressed as a series of action combinations, but those skilled in the art should be aware that the present application is not limited by the described order of actions, because according to the present application, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily required by the present application.

[0172] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0173] In the several embodiments provided in the present application, it should be understood that the disclosed device can be implemented in other ways. For example, the device embodiments described above are only schematic, such as the division of the above-mentioned units, which is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, and the indirect coupling or communication connection of devices or units can be electrical or other forms.

[0174] The units described above as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0175] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0176] If the above-mentioned integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable memory. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a memory, including a number of instructions to enable a computer device (which can be a personal computer, server or network device, etc.) to execute all or part of the steps of the above-mentioned methods in each embodiment of the present application. The aforementioned memory includes: U disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), mobile hard disk, disk or optical disk and other media that can store program codes.

[0177] Those skilled in the art will appreciate that all or part of the steps in the various methods of the above embodiments may be completed by instructing related hardware through a program, and the program may be stored in a computer-readable memory, which may include a flash drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, etc.

[0178] The embodiments of the present application are introduced in detail above. Specific examples are used in this article to illustrate the principles and implementation methods of the present application. The description of the above embodiments is only used to help understand the method and core idea of ​​the present application. At the same time, for general technical personnel in this field, according to the idea of ​​the present application, there will be changes in the specific implementation method and application scope. In summary, the content of this specification should not be understood as a limitation on the present application.

Claims

1. An information retrieval method, characterized in that: The method comprises: Acquire a target keyword set, wherein the target keyword set includes at least one keyword, and the keyword is at least one of the following: text, icon, character string, calculation formula, and the target keyword set is input by the user; Determining a target complexity corresponding to the target keyword set; Determine a target retrieval control parameter corresponding to the target complexity, the retrieval control parameter is used to control the speed and accuracy of the retrieval algorithm; different complexities correspond to different complexity levels, and different complexity levels correspond to different retrieval control parameters; Performing a search according to the target search control parameters to obtain a target search result; Wherein, determining the target complexity corresponding to the target keyword set includes: Classifying the keywords in the target keyword set to obtain P categories of keywords, where P is a positive integer; According to the preset mapping relationship between the category and the complexity evaluation value, determine the complexity evaluation value corresponding to each category of the P categories of keywords to obtain P complexity evaluation values; determining the number of keywords in the target keyword set; Determine the quantity ratio of each type of keywords in the P types of keywords according to the quantity of keywords and the P types of keywords to obtain P quantity ratios; The target complexity is determined according to the P complexity evaluation values ​​and the P quantity proportions.

2. The method according to claim 1, characterized in that The determining of the target retrieval control parameter corresponding to the target complexity includes: Determine the target algorithm type identifier corresponding to the target complexity according to the mapping relationship between the preset complexity and the algorithm type identifier; Acquire corresponding reference algorithm control parameters according to the target algorithm type identifier; Determine the popularity value corresponding to each keyword in the target keyword set to obtain multiple popularity values; Determine a heat average value according to the multiple heat values; Determine the popularity value corresponding to each keyword in the P categories of keywords to obtain P popularity values; Determine a target mean square error according to the P heat values; According to a preset mapping relationship between the mean square error and the optimization coefficient, a target optimization coefficient corresponding to the target mean square error is determined; Optimizing the heat mean according to the target optimization coefficient to obtain a reference heat mean; According to the preset mapping relationship between the heat average and the adjustment coefficient, determine the target adjustment coefficient corresponding to the reference heat average; Adjusting the reference algorithm control parameter according to the target adjustment coefficient to obtain a target algorithm control parameter; The target algorithm type identifier and the target algorithm control parameter are used as the target retrieval control parameter.

3. The method according to any one of claims 1 to 2, characterized in that: The step of obtaining a target keyword set includes: Get the target image; Performing character recognition on the target image to obtain target text; Perform keyword extraction on the target text to obtain x first keywords, where x is an integer greater than 1; Performing icon recognition on the target image to obtain Q icons, where Q is a natural number; According to a preset mapping relationship between icons and keywords, determine the keyword corresponding to each of the Q icons to obtain y second keywords; The x first keywords and the y second keywords are used as the target keyword set.

4. The method according to any one of claims 1 to 2, characterized in that: The step of performing a search according to the target search control parameter to obtain a target search result includes: Get the user's target identity level; Determine the target database identifier corresponding to the target identity level according to the preset mapping relationship between the identity level and the database identifier; The database corresponding to the target database identifier is searched according to the target search control parameter to obtain the target search result.

5. The method according to claim 3, characterized in that: The step of performing a search according to the target search control parameter to obtain a target search result includes: Get the user's target identity level; Determine the target database identifier corresponding to the target identity level according to the preset mapping relationship between the identity level and the database identifier; The database corresponding to the target database identifier is searched according to the target search control parameter to obtain the target search result.

6. An information retrieval device, characterized in that: The device comprises: an acquisition unit, a first determination unit, a second determination unit and a retrieval unit, wherein: The acquisition unit is used to acquire a target keyword set, wherein the target keyword set includes at least one keyword, and the keyword is at least one of the following: text, icon, character string, calculation formula; the target keyword set is input by the user; The first determining unit is used to determine the target complexity corresponding to the target keyword set; The second determining unit is used to determine the target retrieval control parameter corresponding to the target complexity; The retrieval unit is used to perform retrieval according to the target retrieval control parameter to obtain the target retrieval result, and the retrieval control parameter is used to control the speed and accuracy of the retrieval algorithm; different complexities correspond to different complexity levels, and different complexity levels correspond to different retrieval control parameters; Wherein, in determining the target complexity corresponding to the target keyword set, the first determining unit is specifically used to: Classifying the keywords in the target keyword set to obtain P categories of keywords, where P is a positive integer; According to the preset mapping relationship between the category and the complexity evaluation value, determine the complexity evaluation value corresponding to each category of the P categories of keywords to obtain P complexity evaluation values; determining the number of keywords in the target keyword set; Determine the quantity ratio of each type of keywords in the P types of keywords according to the quantity of keywords and the P types of keywords to obtain P quantity ratios; The target complexity is determined according to the P complexity evaluation values ​​and the P quantity proportions.

7. An electronic device, characterized in that: The method comprises a processor and a memory, wherein the memory is used to store one or more programs and is configured to be executed by the processor, wherein the program comprises instructions for executing the steps in the method according to any one of claims 1 to 5.

8. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, wherein the computer program enables a computer to execute the method according to any one of claims 1 to 5.

9. A computer program product, characterized in that The computer program product enables a computer to execute the method according to any one of claims 1 to 5.

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