Information processing method and information processing device

Abstract

The present application discloses an information processing method and an information processing device, which belongs to the field of communication technology. The information processing method includes: receiving a first input of a search text from a user; in response to the first input, dividing the search text into at least one text segmentation, and determining the word weight value of each text segmentation; obtaining an application associated with each text segmentation, and obtaining an index domain weight value of each application; determining a search score for each application according to the word weight value of the text segmentation and the index domain weight value of the application; displaying N applications according to the search score, where N is a positive integer; wherein the application associated with the text segmentation is an application whose application name contains the text segmentation.

Description

Technical Field

[0001] The present application belongs to the field of communication technology, and specifically relates to an information processing method and an information processing device. Background Art

[0002] When users search for applications through the app store, they often enter long-tail words or question-and-answer search texts. For example, when a user enters "I want to download chess", the user's real intention is to download an application containing the keyword "chess".

[0003] However, in the related art, when using search methods (such as tf-idf algorithm, BM25 algorithm, etc.) to perform term frequency (tf) and inverse document frequency (idf) analysis, since the frequency of the word "I want" in all documents is lower than that of "chess", its idf value is higher than that of "chess", then Figure 1 As shown, the applications containing "I want" in the returned search results are ranked at the front, resulting in the problem that the searched applications do not meet the user's actual search intention. Summary of the invention

[0004] The purpose of the embodiments of the present application is to provide an information processing method and an information processing device, which can solve the problem in the related art that the application programs searched out do not meet the user's actual search intention.

[0005] In a first aspect, an embodiment of the present application provides an information processing method, the information processing method comprising:

[0006] Receiving a first input of a search text from a user;

[0007] In response to the first input, the search text is divided into at least one text segmentation, and a word weight value of each text segmentation is determined;

[0008] Obtain the application associated with each text segmentation, and obtain the index domain weight value of each application;

[0009] Determine the search score of each application according to the word weight value of the text segmentation and the index domain weight value of the application;

[0010] Display N applications based on the search score, where N is a positive integer;

[0011] The application associated with the text segmentation is an application whose application name contains the text segmentation.

[0012] In a second aspect, an embodiment of the present application provides an information processing device, the information processing device comprising:

[0013] A receiving module, used for receiving a first input of a search text by a user;

[0014] A segmentation module, configured to segment the search text into at least one text segmentation in response to a first input;

[0015] A determination module, used to determine the word weight value of each text segmentation word;

[0016] An acquisition module is used to acquire the application associated with each text segmentation and to acquire the index domain weight value of each application;

[0017] The determination module is further used to determine the search score of each application according to the word weight value of the text segmentation and the index domain weight value of the application;

[0018] A display module, used for displaying N applications according to the search scores, where N is a positive integer;

[0019] The application associated with the text segmentation is an application whose application name contains the text segmentation.

[0020] In a third aspect, an embodiment of the present application provides an electronic device, which includes a processor, a memory, and a program or instruction stored in the memory and executable on the processor, wherein the program or instruction, when executed by the processor, implements the steps of the method of the first aspect.

[0021] In a fourth aspect, an embodiment of the present application provides a readable storage medium, on which a program or instruction is stored, and when the program or instruction is executed by a processor, the steps of the method of the first aspect are implemented.

[0022] In a fifth aspect, an embodiment of the present application provides a chip, the chip including a processor and a communication interface, the communication interface and the processor are coupled, and the processor is used to run programs or instructions to implement the method of the first aspect.

[0023] In an embodiment of the present application, after receiving the search text input by the user, the electronic device performs a segmentation operation on the search text, thereby dividing the search text into at least one text segmentation, and calculating the word weight value of each text segmentation according to the segmentation characteristics of the text segmentation, so as to realize the semantic analysis of the search text. For each text segmentation, one or more pre-stored applications associated with the text segmentation are obtained, and the pre-stored index domain weight value of each application is obtained. Further, according to the word weight value of the text segmentation obtained above and the index domain weight value of the application, the search score of each application is determined, and the application is sorted by the search score. Specifically, N applications whose search scores are greater than or equal to the preset score threshold are obtained, and these N applications are arranged in order from high to low according to the search scores and displayed to the user. In the above manner, the search score of the application can be calculated by combining the segmentation word weight of the search text and the index domain weight value of the application, that is, the degree of association between the application and the search text is determined, so as to display the application that is more in line with the user's real search intention to the user, and meet the user's search needs. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 is a schematic diagram of a search display interface of an electronic device in the related art;

[0025] Figure 2 It is one of the flowcharts of the information processing method of the embodiment of the present application;

[0026] Figure 3 is a schematic diagram of an inverted index chain for text segmentation in an embodiment of the present application;

[0027] Figure 4 is a schematic diagram of a search display interface of an electronic device in an embodiment of the present application;

[0028] Figure 5 This is the second flowchart of the information processing method of the embodiment of the present application;

[0029] Figure 6 is a schematic block diagram of an information processing device according to an embodiment of the present application;

[0030] Figure 7 It is one of the schematic block diagrams of the electronic device according to the embodiment of the present application;

[0031] Figure 8 This is the second schematic block diagram of the electronic device according to the embodiment of the present application. DETAILED DESCRIPTION

[0032] The following will be combined with the drawings in the embodiments of the present application to clearly describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, rather than all the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments in the present application belong to the scope of protection of this application.

[0033] The terms "first", "second", etc. in the specification and claims of the present application are used to distinguish similar objects, and are not used to describe a specific order or precedence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present application can be implemented in an order other than those illustrated or described here. In addition, "and / or" in the specification and claims represents at least one of the connected objects, and the character " / " generally represents that the objects associated with each other are in an "or" relationship.

[0034] The information processing method, information processing device, electronic device and readable storage medium provided by the embodiments of the present application are described in detail below with reference to the accompanying drawings through specific embodiments and their application scenarios.

[0035] The present application embodiment provides an information processing method, such as Figure 2 As shown, the information processing method includes:

[0036] Step 202, receiving a first input of a search text from a user;

[0037] Step 204, in response to the first input, divide the search text into at least one text segmentation, and determine a word weight value of each text segmentation;

[0038] Step 206, obtaining the application associated with each text segmentation, and obtaining the index domain weight value of each application;

[0039] Step 208, determining the search score of each application program according to the word weight value of the text segmentation and the index domain weight value of the application program;

[0040] Step 210, displaying N applications according to the search scores, where N is a positive integer;

[0041] The application associated with the text segmentation is an application whose application name contains the text segmentation.

[0042] In this embodiment, an application store APP is installed in the electronic device. The user enters a search text in the application store APP. The electronic device determines the APPs that match the search text based on the search text entered by the user and displays them to the user. The user can select one or more of them for download and installation.

[0043] Specifically, after receiving the search text input by the user, the electronic device performs a segmentation operation on the search text, thereby dividing the search text into at least one text segmentation, and calculating the word weight value of each text segmentation according to the segmentation features of the text segmentation, thereby realizing semantic analysis of the search text. For example, for the user input "I want to download chess", Hanlp (an open source segmentation tool) is used for segmentation to obtain four text segmentations of "I", "want", "download", and "chess", and the word weight value of each text is calculated.

[0044] For each text segmentation, obtain one or more pre-stored applications (i.e., candidate applications) associated with the text segmentation, and obtain the pre-stored index domain weight value corresponding to the text segmentation for each application. The index domain weight value of the application refers to the importance of the application to the text segmentation associated with it. It should be noted that the application associated with the text segmentation is the application whose application name contains the text segmentation. For example, for the text segmentation "chess", the application associated with it can be "Everyday Chess", "Chess Assistant", "Chess", etc.

[0045] For example, Figure 3 As shown, an inverted index chain containing M APPs (i.e., doc) corresponding to each text segmentation is pre-stored, and each doc contains an application unique identification code (APPid), an application name (APPName), multiple hit index domain lists (indexFields), and an offline score (i.e., the quality score of the APP dimension). Among them, each hit index domain list records the index domain, index domain weight, offset, length, and idf value of the application. It should be noted that the inverted index chain is sorted according to the offline score, that is, the offline scores of doc1, doc2...docM decrease in sequence. If the number of APPs corresponding to the text segmentation is too large, the offline score can be used for truncation, for example, retaining applications with offline scores greater than or equal to the first preset score threshold, and removing applications with offline scores less than the first preset score threshold. The applications associated with the text segmentation and the index domain weight value of each application can be obtained through the inverted index chain.

[0046] Furthermore, according to the word weight value of the text segmentation and the index domain weight value of the application, the search score of each application is determined, and the application is sorted by the search score. Specifically, N applications whose search scores are greater than or equal to the second preset score threshold are obtained, and these N applications are arranged in descending order according to the search scores and displayed to the user. For example, Figure 4As shown, for the search text "I want to download chess" input by the user, the applications containing the word "chess" are ranked first in the final displayed results.

[0047] Through the above method, the search score of the application can be calculated by combining the segmentation word weight of the search text and the index domain weight value of the application, that is, the degree of association between the application and the search text is determined, so as to display applications that are more in line with the user's real search intention and meet the user's search needs.

[0048] Furthermore, in one embodiment of the present application, determining the word weight value of each text segmentation includes: when displaying multiple word segmentation feature identifiers, receiving a second input from a user for at least one target identifier among the multiple word segmentation feature identifiers, wherein the word segmentation feature identifier indicates a word segmentation feature of the text segmentation by the user; in response to the second input, determining a target word segmentation feature corresponding to the target identifier; receiving a third input from the user for inputting a feature weight value of the target word segmentation feature; and in response to the third input, calculating the word weight value of the text segmentation based on the score of the target word segmentation feature and the feature weight value of the target word segmentation feature.

[0049] In this embodiment, the word weight value of the text segmentation is calculated according to the word segmentation features and feature weight values ​​of the text segmentation, and the word segmentation features of the text segmentation and the feature weight values ​​of each word segmentation feature can be selected by the user. Specifically, multiple word segmentation feature identifiers are displayed on the electronic device, one word segmentation feature identifier represents a word segmentation feature, and each word segmentation feature corresponds to a default score in advance. The user selects one or more of the multiple word segmentation feature identifiers, and then sets the feature weight value for each selected target word segmentation feature. Exemplarily, the electronic device displays "part of speech", "word location", "word frequency", "word length", and other word segmentation features, and the user selects "part of speech", "word location", "word frequency" and "word length", and sets the feature weight value of "part of speech" to 0.3, the feature weight value of "word location" to 0.3, the feature weight value of "word frequency" to 0.2, and the feature weight value of "word length" to 0.2.

[0050] Further, according to the score of the target word segmentation feature and the feature weight value of the target word segmentation feature, the word weight value of the text word segmentation is calculated according to the formula f(x) = part of speech score × x1 + word position score × x2 + idf word frequency score × x3 + word length score × x4. Among them, f(x) is the word weight value, x1 represents the feature weight value of "part of speech", x2 represents the feature weight value of "word position", x3 represents the feature weight value of "word frequency", and x4 represents the feature weight value of "word length". For example, for the search text "I want to download chess" input by the user, through the above calculation method, it can be calculated that the word weight value of "chess" is 0.36466, the word weight value of "download" is 0.34313, the word weight value of "want" is 0.18739, and the word weight value of "I" is 0.10479. Obviously, the word weight value of "chess" is significantly higher than that of other word segmentations, that is, it is determined that "chess" is more in line with the understanding of the user's intention.

[0051] Through the above method, users can select the word segmentation features of text segmentation and set the weight values ​​of the word segmentation features by themselves, that is, they can more flexibly customize the word weight values ​​of text segmentation, so as to more accurately predict user search intentions and determine more accurate applications.

[0052] In some embodiments, the idf value may be used as a weak feature to calculate the word weight value of text segmentation.

[0053] Furthermore, in one embodiment of the present application, the search score of each application is determined based on the word weight value of the text segmentation and the index domain weight value of the application, including: calculating the score of the text segmentation contained in the application name of the application based on the word weight value of the text segmentation and the index domain weight value of the application associated with the text segmentation; calculating the segmentation score of the application based on the score of each text segmentation contained in the application name of the application; determining the intersection segmentation and union segmentation of the text segmentation contained in the search text and the name segmentation contained in the application name of the application; calculating the segmentation similarity of the application based on the intersection segmentation and the union segmentation; and calculating the search score of the application based on the segmentation score of the application and the segmentation similarity of the application.

[0054] In this embodiment, the text segmentation contained in the application name of the application is determined, and the score of the text segmentation is calculated according to the word weight value of the text segmentation and the index domain weight value of the application associated with the text segmentation. Exemplarily, the search text entered by the user is "I want to download chess", and for the application "Everyday Chess", the text segmentation contained in its name is "chess" and "play", then the scores of "chess" and "play" are calculated. Specifically, the index domain weight values ​​of the applications associated with "chess" and "play" are determined respectively, and the score of "chess" is calculated according to the word weight value of "chess" and the index domain weight value of the application associated with "chess", and the score of "play" is calculated according to the word weight value of "play" and the index domain weight value of the application associated with "play". It should be noted that the applications associated with "chess" and "play" include "Everyday Chess", but are not limited to "Everyday Chess".

[0055] The comprehensive score of each text segmentation contained in the application name of the application is used as the segmentation score of the application. For example, the comprehensive score of "chess" and "play" is used as the segmentation score of "play chess every day".

[0056] Further, determine the intersection segmentation and union segmentation of the text segmentation contained in the search text and the name segmentation contained in the application name of the application, and calculate the segmentation similarity of the application based on the intersection segmentation and the union segmentation. Exemplarily, the text segmentation contained in the search text "I want to download chess" is "I", "I want", "download", "chess", and the name segmentation contained in the application name of the application "Everyday chess" is "Everyday", "Download", "Chess", then the intersection segmentation is "Download" and "Chess", and the union segmentation is "I", "I want", "Download", "Chess", "Everyday". Calculate the segmentation similarity of the application, that is, calculate the Jaccard coefficient of the name segmentation contained in the application name of the application and the text segmentation contained in the search text, which is equal to the intersection segmentation / union segmentation, that is, equal to 1 / 3.

[0057] Finally, the search score of the application is calculated based on the segmentation score of the application and the segmentation similarity of the application, for example, using the formula: search score = segmentation similarity × 0.3 + segmentation score × 0.7, where 0.3 and 0.7 are weight coefficients that can be set by the user.

[0058] Through the above method, the search score of the application can be calculated by combining the segmentation word weight of the search text and the index domain weight value of the application, so as to display the application that is more in line with the user's real search intention.

[0059] Furthermore, in one embodiment of the present application, the score of the text segmentation contained in the application name of the application is calculated based on the word weight value of the text segmentation and the index domain weight value of the application associated with the text segmentation, including: when the number of applications associated with the text segmentation is multiple, the score of the text segmentation is calculated based on the word weight value of the text segmentation and the index domain weight value of the first target application; wherein the first target application is an application whose index domain weight value is greater than or equal to a first threshold.

[0060] In this embodiment, if a text segmentation is associated with an application, the score of the text segmentation is calculated based on the word weight value of the text segmentation and the index domain weight value of the application. If a text segmentation is associated with multiple applications, the score of the text segmentation is calculated based on the word weight value of the text segmentation and the largest index domain weight value among the multiple applications. Exemplarily, the applications associated with the text segmentation "chess" include "Everyday Chess", "Everyone Chess", "Chess Assistant", etc., and the maximum value of the index domain weight value of the associated application is used as the calculation parameter for calculating the score of the text segmentation.

[0061] For example, the score of the text segmentation is calculated according to the formula: score of the text segmentation = word weight value × maximum value of the index domain weight value. Alternatively, the score of the text segmentation is calculated according to the formula: score of the text segmentation = word weight value × (0.75 × maximum value of the index domain weight value + 0.25 × offset score), where the offset score is the offset corresponding to the maximum index domain weight value.

[0062] Through the above method, the application with the greatest correlation with the text segmentation (that is, the application with the largest index domain weight value) is determined among multiple associated applications of the text segmentation, and the index domain weight value of the application with the greatest correlation is used to calculate the score of the text segmentation, so that the calculation of the score of the text segmentation can be more accurate, and then the application that better meets the user's actual search intention can be obtained based on the score of the text segmentation.

[0063] Furthermore, in one embodiment of the present application, obtaining the application associated with each text segmentation includes: in the case where multiple text segmentations are associated with one application, determining the index domain weight values ​​corresponding to each associated text segmentation of the application; and associating the application as a target text segmentation; wherein the target text segmentation is the text segmentation corresponding to the largest index domain weight value among multiple index domain weight values ​​of the application.

[0064] In this embodiment, for a text segmentation, if the application associated with the text segmentation is also associated with other text segmentations, the index domain weight values ​​corresponding to each associated text segmentation of the application are determined, and the text segmentation corresponding to the maximum value in the index domain weight value (i.e., the target text segmentation) is used as the text segmentation associated with the application. Exemplarily, for the application "Everyday Playing Chess" associated with the text segmentation "chess", the application is also associated with the text segmentation "play", if the index domain weight value of the application corresponding to "chess" is greater than the index domain weight value of the application corresponding to "play", the application "Everyday Playing Chess" is used as the application associated with the text segmentation "chess".

[0065] Through the above method, the direct correlation between text segmentation and application programs can be accurately determined, so that the calculation of text segmentation scores can be more accurate, and then an application program that better meets the user's real search intention can be obtained based on the text segmentation scores.

[0066] In a specific embodiment of the present application, Figure 5 As shown, the information processing method includes:

[0067] Step 502: receiving a search text input by a user.

[0068] Step 504: perform intent analysis on the search text.

[0069] In this step, the search text is divided into a plurality of text segments and a word weight value of each text segment is determined.

[0070] Step 506: perform reverse pull of the application.

[0071] In this step, all candidate applications are identified using the inverted index chain of text segmentation.

[0072] Step 508: Scoring the application.

[0073] In this step, the candidate application is scored by combining the word weight value of the text segmentation and the index domain weight value of the candidate application.

[0074] Step 510, displaying the top N applications according to the scores of the applications.

[0075] In this step, the applications are sorted in order from high to low according to the scores obtained in the previous step, and the top N applications are selected as recommended applications for the search text for display.

[0076] In this embodiment, the search score of the application can be calculated by combining the segmentation word weights of the search text and the index domain weight value of the application, that is, the degree of association between the application and the search text is determined, thereby displaying to the user applications that are more in line with the user's actual search intent and satisfying the user's search needs.

[0077] It should be noted that the information processing method provided in the embodiment of the present application can be executed by an information processing device, or a control module in the information processing device for executing the information processing method. In the embodiment of the present application, the information processing device provided in the embodiment of the present application is described by taking the information processing device executing the information processing method as an example.

[0078] The present application embodiment provides an information processing device, such as Figure 6 As shown, the information processing device 600 includes:

[0079] A receiving module 602 is used to receive a first input of a search text by a user;

[0080] A division module 604, configured to divide the search text into at least one text segmentation in response to the first input;

[0081] A determination module 606 is used to determine a word weight value of each text segmentation;

[0082] An acquisition module 608 is used to acquire the application associated with each text segmentation, and acquire the index domain weight value of each application;

[0083] The determination module 606 is further used to determine the search score of each application program according to the word weight value of the text segmentation and the index domain weight value of the application program;

[0084] Display module 610, used to display N applications according to the search score, where N is a positive integer;

[0085] The application associated with the text segmentation is an application whose application name contains the text segmentation.

[0086] In this embodiment, after receiving the search text input by the user, the electronic device performs a segmentation operation on the search text, thereby dividing the search text into at least one text segmentation, and calculating the word weight value of each text segmentation according to the segmentation characteristics of the text segmentation, so as to realize the semantic analysis of the search text. For each text segmentation, one or more pre-stored applications associated with the text segmentation are obtained, and the pre-stored index domain weight value of each application is obtained. Further, according to the word weight value of the text segmentation obtained above and the index domain weight value of the application, the search score of each application is determined, and the application is sorted by the search score. Specifically, N applications whose search scores are greater than or equal to the preset score threshold are obtained, and these N applications are arranged in order from high to low according to the search scores and displayed to the user. In the above manner, the search score of the application can be calculated by combining the segmentation word weight of the search text and the index domain weight value of the application, that is, the degree of association between the application and the search text is determined, so as to display the application that is more in line with the user's real search intention to the user, and meet the user's search needs.

[0087] Furthermore, in one embodiment of the present application, the receiving module 602 is also used to receive a second input from a user for at least one target identifier among the multiple word segmentation feature identifiers when multiple word segmentation feature identifiers are displayed, wherein the word segmentation feature identifier indicates a word segmentation feature of the text segmentation indicated by the user; the determining module 606 is specifically used to determine a target word segmentation feature corresponding to the target identifier in response to the second input; the receiving module 602 is also used to receive a third input from the user for a feature weight value of the target word segmentation feature; the determining module 606 is specifically used to calculate a word weight value of the text segmentation based on the score of the target word segmentation feature and the feature weight value of the target word segmentation feature in response to the third input.

[0088] Further, in one embodiment of the present application, the determination module 606 is specifically used to: calculate the score of the text segmentation contained in the application name of the application based on the word weight value of the text segmentation and the index domain weight value of the application associated with the text segmentation; calculate the segmentation score of the application based on the score of each text segmentation contained in the application name of the application; determine the intersection segmentation and union segmentation of the text segmentation contained in the search text and the name segmentation contained in the application name of the application; calculate the segmentation similarity of the application based on the intersection segmentation and the union segmentation; calculate the search score of the application based on the segmentation score of the application and the segmentation similarity of the application.

[0089] Further, in one embodiment of the present application, the determination module 606 is specifically used to calculate the score of the text segmentation based on the word weight value of the text segmentation and the index domain weight value of the first target application when the number of applications associated with the text segmentation is multiple; wherein the first target application is an application whose index domain weight value is greater than or equal to the first threshold.

[0090] Further, in one embodiment of the present application, the acquisition module 608 is specifically used to: when multiple text segmentations are associated with one application, determine the index domain weight values ​​corresponding to each associated text segmentation of the application; associate the application as the target text segmentation; wherein the target text segmentation is the text segmentation corresponding to the largest index domain weight value among the multiple index domain weight values ​​of the application.

[0091] The information processing device 600 in the embodiment of the present application can be a device, or a component, integrated circuit or chip in a terminal. The device can be a mobile electronic device or a non-mobile electronic device. Exemplarily, the mobile electronic device can be a mobile phone, a tablet computer, a laptop computer, a PDA, an in-vehicle electronic device, a wearable device, an ultra-mobile personal computer (Ultra-Mobile Personal Computer, UMPC), a netbook or a personal digital assistant (Personal Digital Assistant, PDA), etc., and the non-mobile electronic device can be a server, a network attached storage (Network Attached Storage, NAS), a personal computer (Personal Computer, PC), a television (Television, TV), a teller machine or a self-service machine, etc., which is not specifically limited in the embodiment of the present application.

[0092] The information processing device 600 in the embodiment of the present application may be a device having an operating system. The operating system may be an Android operating system, an iOS operating system, or other possible operating systems, which are not specifically limited in the embodiment of the present application.

[0093] The information processing device 600 provided in the embodiment of the present application can realize Figures 2 to 5 To avoid repetition, the various processes implemented in the information processing method embodiment will not be described again here.

[0094] Optional, such as Figure 7As shown, an embodiment of the present application also provides an electronic device 700, including a processor 702, a memory 704, and a program or instruction stored in the memory 704 and executable on the processor 702. When the program or instruction is executed by the processor 702, each process of the above-mentioned information processing method embodiment is implemented, and the same technical effect can be achieved. To avoid repetition, it will not be described here.

[0095] It should be noted that the electronic devices in the embodiments of the present application include the above-mentioned mobile electronic devices and non-mobile electronic devices.

[0096] Figure 8 A schematic diagram of the hardware structure of an electronic device to implement an embodiment of the present application.

[0097] The electronic device 800 includes but is not limited to components such as a radio frequency unit 802 , a network module 804 , an audio output unit 806 , an input unit 808 , a sensor 810 , a display unit 812 , a user input unit 814 , an interface unit 816 , a memory 818 , and a processor 820 .

[0098] Those skilled in the art will appreciate that the electronic device 800 may also include a power source (such as a battery) for supplying power to each component, and the power source may be logically connected to the processor 820 through a power management system, thereby implementing functions such as managing charging, discharging, and power consumption management through the power management system. Figure 8 The electronic device structure shown in the figure does not constitute a limitation on the electronic device. The electronic device may include more or fewer components than shown in the figure, or combine certain components, or arrange the components differently, which will not be described in detail here.

[0099] Among them, the user input unit 814 is used to receive a first input of the user on the search text; the processor 820 is used to divide the search text into at least one text segmentation in response to the first input, determine the word weight value of each text segmentation, obtain the application associated with each text segmentation, and obtain the index domain weight value of each application, and determine the search score of each application according to the word weight value of the text segmentation and the index domain weight value of the application; the display unit 812 is used to display N applications according to the search score, where N is a positive integer; wherein the application associated with the text segmentation is the application whose application name contains the text segmentation.

[0100] In this embodiment, after receiving the search text input by the user, the electronic device performs a segmentation operation on the search text, thereby dividing the search text into at least one text segmentation, and calculating the word weight value of each text segmentation according to the segmentation characteristics of the text segmentation, so as to realize the semantic analysis of the search text. For each text segmentation, one or more pre-stored applications associated with the text segmentation are obtained, and the pre-stored index domain weight value of each application is obtained. Further, according to the word weight value of the text segmentation obtained above and the index domain weight value of the application, the search score of each application is determined, and the application is sorted by the search score. Specifically, N applications whose search scores are greater than or equal to the preset score threshold are obtained, and these N applications are arranged in order from high to low according to the search scores and displayed to the user. In the above manner, the search score of the application can be calculated by combining the segmentation word weight of the search text and the index domain weight value of the application, that is, the degree of association between the application and the search text is determined, so as to display the application that is more in line with the user's real search intention to the user, and meet the user's search needs.

[0101] Furthermore, in one embodiment of the present application, the user input unit 814 is also used to receive a second input from a user for at least one target identifier among multiple word segmentation feature identifiers when multiple word segmentation feature identifiers are displayed, wherein the word segmentation feature identifier indicates a word segmentation feature of the text segmentation indicated by the user; the processor 820 is specifically used to determine a target word segmentation feature corresponding to the target identifier in response to the second input; the user input unit 814 is also used to receive a third input from a user for inputting a feature weight value of the target word segmentation feature; the processor 820 is specifically used to calculate a word weight value of the text segmentation based on the score of the target word segmentation feature and the feature weight value of the target word segmentation feature in response to the third input.

[0102] Further, in one embodiment of the present application, the processor 820 is specifically used to: calculate the score of the text segmentation contained in the application name of the application based on the word weight value of the text segmentation and the index domain weight value of the application associated with the text segmentation; calculate the segmentation score of the application based on the score of each text segmentation contained in the application name of the application; determine the intersection segmentation and union segmentation of the text segmentation contained in the search text and the name segmentation contained in the application name of the application; calculate the segmentation similarity of the application based on the intersection segmentation and the union segmentation; calculate the search score of the application based on the segmentation score of the application and the segmentation similarity of the application.

[0103] Further, in one embodiment of the present application, the processor 820 is specifically used to calculate the score of the text segmentation based on the word weight value of the text segmentation and the index domain weight value of the first target application when the number of applications associated with the text segmentation is multiple; wherein the first target application is an application whose index domain weight value is greater than or equal to the first threshold.

[0104] Further, in one embodiment of the present application, the processor 820 is specifically used to: when multiple text segmentations are associated with one application, determine the index domain weight values ​​corresponding to each associated text segmentation of the application; associate the application as the target text segmentation; wherein the target text segmentation is the text segmentation corresponding to the largest index domain weight value among the multiple index domain weight values ​​of the application.

[0105] It should be understood that in the embodiment of the present application, the radio frequency unit 802 can be used to send and receive information or send and receive signals during a call, specifically, receive downlink data from a base station or send uplink data to a base station. The radio frequency unit 802 includes but is not limited to an antenna, at least one amplifier, a transceiver, a coupler, a low noise amplifier, a duplexer, etc.

[0106] The network module 804 provides users with wireless broadband Internet access, such as helping users to send and receive emails, browse web pages, and access streaming media.

[0107] The audio output unit 806 can convert the audio data received by the RF unit 802 or the network module 804 or stored in the memory 818 into an audio signal and output it as sound. In addition, the audio output unit 806 can also provide audio output related to a specific function performed by the electronic device 800 (e.g., a call signal reception sound, a message reception sound, etc.). The audio output unit 806 includes a speaker, a buzzer, a receiver, etc.

[0108] The input unit 808 is used to receive audio or video signals. The input unit 808 may include a graphics processing unit (GPU) 8082 and a microphone 8084. The graphics processor 8082 processes the image data of a static picture or video obtained by an image capture device (such as a camera) in a video capture mode or an image capture mode. The processed image frame can be displayed on the display unit 812, or stored in the memory 818 (or other storage medium), or sent via the radio frequency unit 802 or the network module 804. The microphone 8084 can receive sound and can process the sound into audio data. The processed audio data can be converted into a format output that can be sent to a mobile communication base station via the radio frequency unit 802 in the case of a telephone call mode.

[0109] The electronic device 800 also includes at least one sensor 810, such as a fingerprint sensor, a pressure sensor, an iris sensor, a molecular sensor, a gyroscope, a barometer, a hygrometer, a thermometer, an infrared sensor, a light sensor, a motion sensor, and other sensors.

[0110] The display unit 812 is used to display information input by the user or information provided to the user. The display unit 812 may include a display panel 8122, which may be configured in the form of a liquid crystal display, an organic light emitting diode, or the like.

[0111] The user input unit 814 can be used to receive input digital or character information, and to generate key signal input related to user settings and function control of the electronic device. Specifically, the user input unit 814 includes a touch panel 8142 and other input devices 8144. The touch panel 8142 is also called a touch screen, which can collect the user's touch operations on or near it. The touch panel 8142 may include a touch detection device and a touch controller. Among them, the touch detection device detects the user's touch orientation, detects the signal brought by the touch operation, and transmits the signal to the touch controller; the touch controller receives the touch information from the touch detection device, and converts it into contact coordinates, and then sends it to the processor 820, receives the command sent by the processor 820 and executes it. Other input devices 8144 may include but are not limited to physical keyboards, function keys (such as volume control keys, switch keys, etc.), trackballs, mice, and joysticks, which will not be repeated here.

[0112] Furthermore, the touch panel 8142 may be overlaid on the display panel 8122. When the touch panel 8142 detects a touch operation on or near it, it is transmitted to the processor 820 to determine the type of the touch event, and then the processor 820 provides a corresponding visual output on the display panel 8122 according to the type of the touch event. The touch panel 8142 and the display panel 8122 may be two independent components or integrated into one component.

[0113] The interface unit 816 is an interface for connecting an external device to the electronic device 800. For example, the external device may include a wired or wireless headset port, an external power supply (or battery charger) port, a wired or wireless data port, a memory card port, a port for connecting a device with an identification module, an audio input / output (I / O) port, a video I / O port, a headphone port, etc. The interface unit 816 may be used to receive input (e.g., data information, power, etc.) from an external device and transmit the received input to one or more elements within the electronic device 800 or may be used to transmit data between the electronic device 800 and an external device.

[0114] The memory 818 can be used to store software programs and various data. The memory 818 can mainly include a program storage area and a data storage area, wherein the program storage area can store an operating system, an application required for at least one function (such as a sound playback function, an image playback function, etc.), etc.; the data storage area can store data created according to the use of the mobile terminal (such as audio data, a phone book, etc.), etc. In addition, the memory 818 can include a high-speed random access memory, and can also include a non-volatile memory, such as at least one disk storage device, a flash memory device, or other volatile solid-state storage devices.

[0115] The processor 820 performs various functions of the electronic device 800 and processes data by running or executing software programs and / or modules stored in the memory 818 and calling data stored in the memory 818, thereby monitoring the electronic device 800 as a whole. The processor 820 may include one or more processing units; preferably, the processor 820 may integrate an application processor and a modem processor, wherein the application processor mainly processes an operating system, a user interface, and application programs, and the modem processor mainly processes wireless communications.

[0116] An embodiment of the present application also provides a readable storage medium, on which a program or instruction is stored. When the program or instruction is executed by a processor, the various processes of the above-mentioned information processing method embodiment are implemented and the same technical effect can be achieved. To avoid repetition, it will not be repeated here.

[0117] The processor is the processor in the electronic device in the above embodiment. The readable storage medium includes a computer readable storage medium, such as a computer read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0118] An embodiment of the present application further provides a chip, which includes a processor and a communication interface, wherein the communication interface and the processor are coupled, and the processor is used to run programs or instructions to implement the various processes of the above-mentioned information processing method embodiment, and can achieve the same technical effect. To avoid repetition, it will not be repeated here.

[0119] It should be understood that the chip mentioned in the embodiments of the present application can also be called a system-level chip, a system chip, a chip system or a system-on-chip chip, etc.

[0120] It should be noted that, in this article, the term "comprises", "includes" or any other variant thereof is intended to cover non-exclusive inclusion, so that the process, method, article or device including a series of elements includes not only those elements, but also includes other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "including one..." do not exclude the presence of other identical elements in the process, method, article or device including the element. In addition, it should be pointed out that the scope of the method and device in the embodiment of the present application is not limited to performing functions in the order shown or discussed, and may also include performing functions in a substantially simultaneous manner or in reverse order according to the functions involved, for example, the described method may be performed in an order different from that described, and various steps may also be added, omitted, or combined. In addition, the features described with reference to certain examples may be combined in other examples.

[0121] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus a necessary general hardware platform, and of course by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present application, or the part that contributes to the prior art, can be embodied in the form of a computer software product, which is stored in a storage medium (such as ROM / RAM, a disk, or an optical disk), and includes a number of instructions for a terminal (which can be a mobile phone, a computer, a server, or a network device, etc.) to execute the methods described in each embodiment of the present application.

[0122] The embodiments of the present application are described above in conjunction with the accompanying drawings, but the present application is not limited to the above-mentioned specific implementation methods. The above-mentioned specific implementation methods are merely illustrative and not restrictive. Under the guidance of the present application, ordinary technicians in this field can also make many forms without departing from the purpose of the present application and the scope of protection of the claims, all of which are within the protection of the present application.

Claims

1. An information processing method, characterized in that: include: Receiving a first input of a search text from a user; In response to the first input, the search text is divided into at least one text segmentation, and a word weight value of each of the text segmentation is determined; Obtaining an application associated with each of the text segmentations, and obtaining an index domain weight value of each of the applications, wherein the index domain weight value of the application refers to the importance of the application to the text segmentation associated with the application; Determining a search score for each of the applications according to a word weight value of the text segmentation and an index domain weight value of the application; Displaying N of the applications according to the search scores, where N is a positive integer; The application associated with the text segmentation is the application whose application name contains the text segmentation.

2. The information processing method according to claim 1, characterized in that: Determining the word weight value of each of the text segmentations includes: In the case where a plurality of word segmentation feature identifiers are displayed, receiving a second input from a user for at least one target identifier among the plurality of word segmentation feature identifiers, wherein the word segmentation feature identifier indicates a word segmentation feature of the text segmentation by the user; In response to the second input, determining a target word segmentation feature corresponding to the target identifier; Receive a third input of a feature weight value of the target word segmentation feature input by a user; In response to the third input, a word weight value of the text word segmentation is calculated according to the score of the target word segmentation feature and the feature weight value of the target word segmentation feature.

3. The information processing method according to claim 1, characterized in that: Determining the search score of each application according to the word weight value of the text segmentation and the index domain weight value of the application includes: Calculating the score of the text segmentation contained in the application name of the application according to the word weight value of the text segmentation and the index domain weight value of the application associated with the text segmentation; Calculating a word segmentation score of the application program according to a score of each word segment of the text contained in an application name of the application program; Determine the intersection segmentation and union segmentation of the text segmentation included in the search text and the name segmentation included in the application name of the application; Calculating the segmentation similarity of the application according to the intersection segmentation and the union segmentation; The search score of the application is calculated according to the word segmentation score of the application and the word segmentation similarity of the application.

4. The information processing method according to claim 3, characterized in that: The step of calculating the score of the text segmentation contained in the application name of the application according to the word weight value of the text segmentation and the index domain weight value of the application associated with the text segmentation includes: In the case that there are multiple applications associated with the text segmentation, calculating the score of the text segmentation according to the word weight value of the text segmentation and the index domain weight value of the first target application; The first target application is an application whose index domain weight value is greater than or equal to a first threshold.

5. The information processing method according to any one of claims 1 to 4, characterized in that: The step of obtaining an application associated with each of the text segmentations includes: In the case where a plurality of the text segmentations are associated with one application, determining an index domain weight value corresponding to each of the text segmentations associated with the application; Associating the application with the target text segmentation application; The target text segmentation is a text segmentation corresponding to the largest index domain weight value among the multiple index domain weight values ​​of the application.

6. An information processing device, characterized in that: include: A receiving module, used for receiving a first input of a search text by a user; a segmentation module, configured to segment the search text into at least one text segmentation in response to the first input; A determination module, used to determine a word weight value of each of the text segmentations; An acquisition module, used to acquire the application associated with each of the text segmentations, and acquire the index domain weight value of each of the application, wherein the index domain weight value of the application refers to the importance of the application to the text segmentation associated with it; The determination module is further used to determine the search score of each of the applications according to the word weight value of the text segmentation and the index domain weight value of the application; A display module, configured to display N of the applications according to the search scores, where N is a positive integer; The application associated with the text segmentation is the application whose application name contains the text segmentation.

7. The information processing device according to claim 6, characterized in that: The receiving module is further configured to receive a second input from a user on at least one target identifier among the multiple word segmentation feature identifiers when multiple word segmentation feature identifiers are displayed, wherein the word segmentation feature identifier indicates a word segmentation feature of the text segmentation by the user; The determination module is specifically configured to determine, in response to the second input, a target word segmentation feature corresponding to the target identifier; The receiving module is further configured to receive a third input from a user inputting a feature weight value of the target word segmentation feature; The determination module is specifically configured to calculate, in response to the third input, a word weight value of the text word segmentation according to the score of the target word segmentation feature and the feature weight value of the target word segmentation feature.

8. The information processing device according to claim 6, characterized in that: The determining module is specifically used for: Calculating the score of the text segmentation contained in the application name of the application according to the word weight value of the text segmentation and the index domain weight value of the application associated with the text segmentation; Calculating a word segmentation score of the application program according to a score of each word segment of the text contained in an application name of the application program; Determine the intersection segmentation and union segmentation of the text segmentation included in the search text and the name segmentation included in the application name of the application; Calculating the segmentation similarity of the application according to the intersection segmentation and the union segmentation; The search score of the application is calculated according to the word segmentation score of the application and the word segmentation similarity of the application.

9. The information processing device according to claim 8, characterized in that: The determination module is specifically configured to calculate the score of the text segmentation according to the word weight value of the text segmentation and the index domain weight value of the first target application program when the number of applications associated with the text segmentation is multiple; The first target application is an application whose index domain weight value is greater than or equal to a first threshold.

10. The information processing device according to any one of claims 6 to 9, characterized in that: The acquisition module is specifically used for: In the case where a plurality of the text segmentations are associated with one application, determining an index domain weight value corresponding to each of the text segmentations associated with the application; Associating the application with the target text segmentation application; The target text segmentation is a text segmentation corresponding to the largest index domain weight value among the multiple index domain weight values ​​of the application.

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