WO2022135339A1 - 消息内容的输入方法、装置和电子设备 - Google Patents

消息内容的输入方法、装置和电子设备 Download PDF

Info

Publication number
WO2022135339A1
WO2022135339A1 PCT/CN2021/139657 CN2021139657W WO2022135339A1 WO 2022135339 A1 WO2022135339 A1 WO 2022135339A1 CN 2021139657 W CN2021139657 W CN 2021139657W WO 2022135339 A1 WO2022135339 A1 WO 2022135339A1
Authority
WO
WIPO (PCT)
Prior art keywords
information
word
recommended
recommendation
recommended word
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Ceased
Application number
PCT/CN2021/139657
Other languages
English (en)
French (fr)
Inventor
赵苗苗
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Vivo Mobile Communication Co Ltd
Original Assignee
Vivo Mobile Communication Co Ltd
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Vivo Mobile Communication Co Ltd filed Critical Vivo Mobile Communication Co Ltd
Publication of WO2022135339A1 publication Critical patent/WO2022135339A1/zh
Anticipated expiration legal-status Critical
Ceased legal-status Critical Current

Links

Images

Classifications

    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F3/00—Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
    • G06F3/01—Input arrangements or combined input and output arrangements for interaction between user and computer
    • G06F3/02—Input arrangements using manually operated switches, e.g. using keyboards or dials
    • G06F3/023—Arrangements for converting discrete items of information into a coded form, e.g. arrangements for interpreting keyboard generated codes as alphanumeric codes, operand codes or instruction codes
    • G06F3/0233—Character input methods
    • G06F3/0236—Character input methods using selection techniques to select from displayed items
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/90—Details of database functions independent of the retrieved data types
    • G06F16/95—Retrieval from the web
    • G06F16/953—Querying, e.g. by the use of web search engines
    • G06F16/9535—Search customisation based on user profiles and personalisation
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/90—Details of database functions independent of the retrieved data types
    • G06F16/95—Retrieval from the web
    • G06F16/953—Querying, e.g. by the use of web search engines
    • G06F16/9537—Spatial or temporal dependent retrieval, e.g. spatiotemporal queries
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/90—Details of database functions independent of the retrieved data types
    • G06F16/95—Retrieval from the web
    • G06F16/953—Querying, e.g. by the use of web search engines
    • G06F16/9538—Presentation of query results

Definitions

  • the present application belongs to the field of communication technologies, and in particular relates to an input method, an apparatus and an electronic device.
  • the input of message content will be involved, and users will input the same or similar message content through the same application in a fixed time period and in a fixed scenario, for example, often through lunchtime
  • the chat software inputs "go to dinner", and sends "go to the meeting room for a meeting, time xx, location xx" during the meeting time period. If the user manually enters these same or similar message content every day, the input process will be very cumbersome and the input efficiency will be Low.
  • the input engine in the related art adds shortcut phrases or common words.
  • the user can select the desired input content from the shortcut phrases or common words provided by the input engine, or the user can The actual requirement is to manually add common words, and select the appropriate common words as the message content to be input when inputting the message content.
  • the input method provided by the input engine in the related art either requires the user to manually set the recommendation information, or is fixed recommendation information provided by the system, and the method of the recommendation information is not flexible enough and the accuracy is poor.
  • the purpose of the embodiments of the present application is to provide an information recommendation method, which can solve the problems of inflexibility and poor accuracy of content recommended based on an input engine in the related art.
  • an information recommendation method which includes:
  • the display interface of the electronic device includes an input area
  • acquire first scene information corresponding to the display interface where the first scene information includes the application to which the display interface belongs and the time included in the display interface at least one of information, the geographic location of the electronic device;
  • M pieces of target recommendation information are displayed based on the first recommendation word and the second recommendation word.
  • an information recommendation device comprising:
  • a first scene information acquisition module configured to acquire first scene information corresponding to the display interface when the display interface of the electronic device includes an input area, where the first scene information includes the application to which the display interface belongs at least one of a program, time information contained in the display interface, and a geographic location of the electronic device;
  • a recommended word determination module configured to determine a first recommended word according to the first scene information, and determine a second recommended word corresponding to the first recommended word;
  • a target recommendation information output module configured to display M pieces of target recommendation information based on the first recommendation word and the second recommendation word.
  • embodiments of the present application provide an electronic device, the electronic device includes a processor, a memory, and a program or instruction stored on the memory and executable on the processor, the program or instruction being The processor implements the steps of the method according to the first aspect when executed.
  • an embodiment of the present application provides a readable storage medium, where a program or an instruction is stored on the readable storage medium, and when the program or instruction is executed by a processor, the steps of the method according to the first aspect are implemented .
  • an embodiment of the present application provides a chip, the chip includes a processor and a communication interface, the communication interface is coupled to the processor, and the processor is configured to run a program or an instruction, and implement the first aspect the method described.
  • the display interface of the electronic device when the display interface of the electronic device includes an input area, the first scene information corresponding to the display interface is obtained, the first recommended word is determined according to the first scene information, and the first recommended word is determined according to the first scene information.
  • Fig. 1a is a flowchart of the specific steps of an information recommendation method provided in Embodiment 1 of the present application;
  • FIG. 1b is a flowchart of the specific steps of another information recommendation method provided in Embodiment 1 of the present application;
  • FIG. 2 is a flowchart of the specific steps of an information recommendation method provided in Embodiment 2 of the present application;
  • Embodiment 3 is a display diagram of a second recommended word provided in Embodiment 2 of the present application.
  • FIG. 4 is a display diagram of a first recommended word provided in Embodiment 2 of the present application.
  • FIG. 5 is a structural diagram of an information recommendation apparatus provided in Embodiment 3 of the present application.
  • FIG. 6 is a structural diagram of an information recommendation apparatus provided in Embodiment 4 of the present application.
  • FIG. 7 is a structural diagram of an electronic device provided in Embodiment 5 of the present application.
  • FIG. 8 is a schematic diagram of a hardware structure of an electronic device according to Embodiment 5 of the present application.
  • FIG. 1a shows the specific steps of an information recommendation method provided in Embodiment 1 of the present application.
  • Step 101 In the case that the display interface of the electronic device includes an input area, obtain first scene information corresponding to the display interface.
  • the information recommendation method in the embodiment of the present application can be applied to electronic equipment, and the electronic equipment can be a mobile terminal, such as a mobile phone, a tablet computer, a notebook computer, a palmtop computer, a vehicle electronic device, a wearable device, an ultra-mobile personal computer (ultra-mobile personal computer) mobile personal computer (UMPC), netbook or personal digital assistant (Personal Digital Assistant, PDA), or the like, or the electronic device may also be a server, a network attached storage (NetworkAttached Storage, NAS), a personal computer (Personal Computer, PC), A non-mobile electronic device such as a television (Television, TV), a teller machine, or a self-service machine is not specifically limited in this embodiment of the present application, and a mobile terminal is used as an example for description in this embodiment of the present application.
  • a mobile terminal is used as an example for description in this embodiment of the present application.
  • the display interface of the mobile terminal is detected in real time. If it is detected that the display interface of the mobile terminal includes an input area, it means that the user needs to recommend information, such as word recommendation, sentence recommendation, etc. At this time, the display interface is obtained. information of the first scene. For example, when it is detected that the display interface is a WeChat chat interface and includes a chat input area, first scene information corresponding to the WeChat chat interface is acquired, so as to determine target recommendation information to be recommended according to the first scene information.
  • the first scene information includes at least one of an application to which the display interface belongs, time information included in the display interface, and a geographic location of the electronic device.
  • the electronic device can determine the application to which the display interface belongs, for example, determine whether the display interface belongs to the chat interface of chat software, the search interface of the input engine, or the search interface of shopping software Search interface, etc.
  • the content frequently input by the user is also different. Therefore, in this embodiment of the present application, different target recommendation information may be determined according to different application programs to which the display interface belongs. For different time periods, users often enter different content. For example, at around 12:00 noon, users often enter "where to eat", and on Monday morning, users often enter content about meeting notices.
  • the embodiment of the present application can be used in When the display interface of the electronic device includes an input area, the current location of the user is determined by determining the geographic location of the electronic device, and then different target recommendation information is determined for different locations.
  • Step 102 Determine a first recommended word according to the first scene information, and determine a second recommended word corresponding to the first recommended word.
  • the user will input some same or similar content in certain fixed time periods, or fixed scenarios, or in a specific application, for example, send "Go to XXX meeting room for a meeting, time XXX; location every Monday morning. XXX; Participant XXX, topic XXX", at around 12 noon, enter information such as "Let's go to XXX for dinner” through chat software.
  • the embodiment of the present application acquires the user's historical up-screen information and the historical up-screen information under the condition that the user's authorization to obtain user information is received.
  • Corresponding second scene information according to the obtained historical screen information and second scene information, generate the user's recommended thesaurus, the recommended thesaurus includes the preset first recommended word and the second recommended word, and the preset first recommended word and second recommended word.
  • the first recommended word corresponds to the second scene information. Therefore, when it is detected that the display interface includes an input box, the first recommended word corresponding to the second scene information that matches the first scene information corresponding to the display interface and the first recommended word corresponding to the first recommended word can be searched in the recommended vocabulary. Second recommendation.
  • the first recommended word is determined according to high-frequency sentences that appear in the user's historical on-screen messages and the second scene information corresponding to the high-frequency sentences, and the high-frequency sentences that have the same or similar second scene information
  • the same or semantically similar keywords contained in this application are in the embodiments of the present application. For example, users often send messages such as "I want to eat hot pot”, “I want to eat barbecue”, “I want to eat crayfish” and so on through chat software on weekend afternoons.
  • high-frequency sentences generally include both the first recommendation word and the second recommendation word, and the second recommendation word is specific content or options corresponding to the first recommendation word.
  • “Crayfish” are the second recommendation words corresponding to the first recommendation word “I want to eat”.
  • Step 103 Display M pieces of target recommendation information based on the first recommendation word and the second recommendation word.
  • the first recommendation word and the second recommendation word are extracted from the high-frequency sentences of the user, and the first recommendation word and the second recommendation word alone do not constitute a complete Therefore, the first recommendation word and the second recommendation word that need to be determined are combined according to the corresponding relationship between the two to generate target recommendation information that includes both the first recommendation word and the second recommendation word.
  • the obtained first scene information corresponding to the user's calling operation to the input engine is "weekend afternoon, chat software”
  • a second scene matching the first scene information is found in the preset recommended vocabulary
  • the first recommendation word corresponding to the information is "want to eat”
  • the second recommendation word corresponding to the first recommendation word is "hot pot”, “barbecue”, “crayfish”
  • the first recommendation word “want to eat” Combine “eat” with these second recommendation words to generate target recommendation information "I want to eat hot pot”, “I want to eat barbecue”, “I want to eat crayfish”, and the generated target recommendation information is displayed in the recommendation display area for users to choose. .
  • the display interface when the display interface includes an input area, the first scene information corresponding to the display interface is obtained, the first recommended word is determined according to the first scene information, and the first recommended word is determined according to the first scene information.
  • the second recommendation word corresponding to the first recommendation word M pieces of target recommendation information are displayed based on the first recommendation word and the second recommendation word, and the target recommendation information can be determined according to the scene information, which improves the determined target recommendation information. real-time and accurate.
  • step 103 After the target recommendation information is displayed, input may be made based on the target recommendation information. Referring to FIG. 1b, after step 103, it may further include:
  • Step 104 in response to the triggering operation on the target recommendation information, generate target information according to the target recommendation information.
  • the target information can be generated according to the first recommendation word and the second recommendation word contained in the target recommendation information. For example, after receiving the user's trigger operation on the target recommendation information "I want to eat hot pot", the target information "I want to eat hot pot” can be directly generated, and the user's behavioral habits can be further analyzed. According to the user's behavioral habits, such as the commonly used tone Words, emoticons, etc., further optimize the target recommendation information to generate target information, such as "I really want to eat hot pot". It is also possible to obtain nearby businesses that meet the user's needs according to the user's current location, and include business information or business locations in the generated target information, for example, "I really want to eat the hot pot in Zhongmao Plaza".
  • Step 105 in the case of receiving the confirmation operation for the target information, input the target information.
  • the target information In generating the target information, it is further judged whether the generated target information meets the user's requirements, and if a user's confirmation operation on the target information is received, the target information is used for input.
  • the generated target information is "I really want to eat hot pot in China Trade Plaza", but the user wants to go to other places, then the user can modify the generated target information, for example, to "I really want to eat Wanda Plaza's hot pot" "Hotpot", the target information is input only when the user's confirmation operation on the target information is received, so as to prevent the input target information from not meeting the user's expectations.
  • the efficiency and accuracy of information input are improved.
  • the execution subject may be an information recommendation device, or a control module in the information recommendation device for executing the information recommendation method.
  • the method provided by the embodiment of the present application is described by taking the information recommending apparatus executing the information recommending method as an example.
  • FIG. 2 it shows the specific steps of an information recommendation method provided in Embodiment 2 of the present application.
  • Step 201 according to the user's historical on-screen information and the second scene information corresponding to the historical on-screen information, generate a recommended thesaurus corresponding to the user, and the recommended thesaurus includes a preset first recommended word and a second recommended word, where the preset first recommended word corresponds to the second scene information.
  • the user's historical screen information and the second scene information corresponding to the historical screen information are obtained, and according to the obtained historical screen information screen information and second scene information, and generate a recommended word bank for the user.
  • the recommended word bank includes preset first recommended words and second recommended words, and the preset first recommended words correspond to the second scene information . Therefore, when the user's calling operation to the input engine is received, the first recommended word corresponding to the second scene information that matches the first scene information corresponding to the calling operation, and the first recommended word corresponding to the first recommended word can be searched in the recommended word database. The corresponding second recommendation word.
  • a recommended vocabulary corresponding to the user is generated, including: :
  • Step S11 determining at least two high-frequency sentences of the user according to the screen-on-screen frequency of the user's historical screen-on-screen information;
  • Step S12 clustering the at least two high-frequency sentences according to the second scene information corresponding to the high-frequency sentences to obtain a high-frequency sentence group;
  • Step S13 determining the first recommended words corresponding to the at least two high-frequency sentences according to the high-frequency sentence group and the preset similarity condition;
  • Step S14 extracting the second inferred word corresponding to the first recommended word in the at least two high-frequency sentences
  • Step S15 Generate a recommended word database corresponding to the user according to the first recommended word and the second recommended word.
  • the embodiments of the present application are aimed at users who often need to input some same or similar content in certain fixed time periods, or in fixed scenarios, or in specific application programs, in order to improve the input
  • the real-time and accuracy of the content recommended by the engine provides an information recommendation method.
  • the recommended words in the embodiments of the present application are all frequently used by the user. Therefore, before determining the recommended word database of the user, it is necessary to determine the high-frequency sentences used by the user.
  • the frequency of the user's previous screen information find at least two historical screen information whose screen access frequency exceeds a preset frequency threshold from the user's historical screen information, and select the at least two previous screen information.
  • the historical on-screen information whose frequency exceeds the preset frequency threshold is taken as at least two high-frequency sentences of the user.
  • Each high-frequency sentence corresponds to a second scene information, and at least two high-frequency sentences are clustered according to the second scene information corresponding to the high-frequency sentence to obtain a high-frequency sentence group.
  • the user's high-frequency sentences are "go to the conference room for a meeting", “want to eat hot pot”, “want to eat barbecue”, “want to eat crayfish” .
  • the second scene information corresponding to "going to the conference room for a meeting” is Monday morning
  • the second scene information corresponding to "I want to eat hot pot", “I want to eat barbecue”, and “I want to eat crayfish” all include weekend afternoons.
  • Cluster these high-frequency sentences according to the second scene information corresponding to the high-frequency sentences and obtain two high-frequency sentence groups.
  • the first recommended word is determined according to the obtained high-frequency sentence group and the preset similarity condition, and the second keyword corresponding to the first keyword in at least two high-frequency sentences is extracted.
  • each high-frequency sentence included in the high-frequency sentence group may be split first to obtain multiple keywords, and these multiple keywords form a keyword set corresponding to the high-frequency sentence group, and the obtained keywords are calculated respectively.
  • the similarity between each keyword in the set that is, the similarity between each two keywords is calculated, and the keywords whose similarity exceeds the preset similarity threshold are combined, and the combined keyword is the high-frequency sentence.
  • the first recommended word corresponding to the group replace the keyword with the preset similarity threshold in the keyword set with the combined keyword, that is, the first recommended word, to obtain an updated keyword set, the updated keyword set , is either the keyword of the first recommended word, or the second recommended word corresponding to the high-frequency sentence group. According to the combination of the first keyword and the second keyword in the high-frequency sentence group in the high-frequency sentence group, the obtained corresponding relationship between each first keyword and each second keyword is determined.
  • the first keyword may be "go to the meeting room”
  • the second keyword may be "meeting”
  • the first keyword may be "meeting”
  • the second keyword is "going to the conference room”. Since this high-frequency sentence group contains only one high-frequency sentence, the first and second recommended words corresponding to the high-frequency sentence group are in one-to-one correspondence.
  • the keywords whose similarity exceeds the preset threshold are "I want to eat”.
  • a recommended word library corresponding to the user is generated according to the obtained first recommended word and second recommended word.
  • the first recommended word corresponds to the second scene information
  • the second recommended word corresponds to the first recommended word.
  • Step 202 in the case that the display interface of the electronic device includes an input area, obtain first scene information corresponding to the display interface.
  • the first scene information includes at least one of an application to which the display interface belongs, time information included in the display interface, and a geographic location of the electronic device where the display interface is located.
  • step 101 For this step, reference may be made to step 101, which is not further described in this embodiment of the present application.
  • Step 203 Search the recommended word database for a first recommended word corresponding to the second scene information that matches the first scene information, and a second recommended word corresponding to the first recommended word.
  • the recommended word database can be searched for the first recommended word corresponding to the second scene information that matches the first scene information corresponding to the display interface, and the first recommended word corresponding to the first recommended word Two recommendation words.
  • the acquired first scene information corresponding to the display interface is "weekend afternoon, chat software”
  • the second recommendation words corresponding to the first recommendation words are "hot pot”, “barbecue”, and "crayfish”.
  • Step 204 displaying M pieces of target recommendation information based on the first recommendation word and the second recommendation word.
  • the first recommended word and the second recommended word are extracted from high-frequency sentences of the user, and the first recommended word and the second recommended word alone do not constitute a completed sentence. Therefore, The first recommended word and the second recommended word to be determined are combined according to the corresponding relationship between the two to generate target recommendation information including both the first recommended word and the second recommended word.
  • the generated target recommendation information is displayed in the recommendation display area for users to choose.
  • the number of the second recommended words corresponding to the first recommended word is greater than 1, and the first recommended word and the second recommended word are combined in step 204.
  • Generate target recommendation information including:
  • Step S21 in at least two second recommendation words corresponding to the first recommendation word, determine a default second recommendation word
  • Step S22 Combine the first recommended word and the default second recommended word to generate target recommendation information.
  • the number of second recommended words corresponding to the first recommended word is greater than 1, according to the user's historical on-screen messages within a preset period, the usage of the second recommended word, and the user's retrieval information on the search engine , browsing information, etc. to determine the weight of the second recommended word, and use the second recommended word with the largest weight value as the default second recommended word.
  • the second recommendation word "hot pot” corresponding to the first recommendation word "good to eat” Among “barbecue” and “crawfish”, "hot pot” has the largest weight value, and "hot pot” is used as the default second recommendation word, and the first recommendation word "good to eat” and the default second recommendation word “hot pot” are compared.
  • the combination generates the target recommendation information "I really want to eat hot pot”.
  • Step 205 in response to the triggering operation on the target recommendation information, generate target information according to the target recommendation information.
  • step 205 in response to the triggering operation on the target recommendation information, target information is generated according to the first recommendation word and the second recommendation word included in the target recommendation word, including :
  • target information is generated according to the first recommendation word and the default second recommendation word.
  • the target information can be generated according to the first recommendation word and the second recommendation word contained in the target recommendation information.
  • the target message "I want to eat” can be directly generated with the target information including the first recommendation word "I want to eat” and the default second recommendation word "Hotpot” "Hotpot” can also further analyze the user's behavioral habits, and further optimize the target recommendation information according to the user's behavioral habits, such as commonly used tone words, emoticons, etc., to generate target information, such as "I really want to eat hotpot". It is also possible to obtain nearby businesses that meet the user's needs according to the user's current location, and include business information or business locations in the generated target information, for example, "I really want to eat the hot pot in Zhongmao Plaza".
  • step 205 in response to the triggering operation on the target recommendation information, target information is generated according to the first recommendation word and the second recommendation word included in the target recommendation information, including :
  • Step S31 displaying at least two second recommendation words corresponding to the first recommendation word in the target recommendation information in response to the triggering operation on the default second recommendation word in the target recommendation information;
  • Step S32 determining the target second recommended word in response to the selection operation on the at least two second recommended words
  • Step S33 Generate target information according to the first recommended word and the target second recommended word.
  • the user can perform a trigger operation on the default second recommended word, for example, click the default second recommended word, and the input engine responds to the user's response to the default second recommended word.
  • the triggering operation of the second recommendation word is to display all the second recommendation words corresponding to the first recommendation word in the target recommendation information in the recommendation display area for the user to select.
  • the target second recommended word is determined, and the target information is generated according to the first recommended word and the target second recommended word.
  • FIG. 3 a presentation diagram of a second recommended word provided by an embodiment of the present application is shown.
  • the determined default second recommended word is "hot pot”, according to the first recommended word and
  • the default recommendation word generates target recommendation information and displays it in the recommendation display area. If the user is not satisfied with the provided default second recommended word "hot pot”, the user can perform a trigger operation on the default second recommended word, for example, click the default recommended word "hot pot”, the input engine will display the first recommended word in the recommendation display area
  • Other second recommendation words corresponding to "I want to eat such as “barbecue”, “crayfish”, “seafood”.
  • the display order of the second recommended words is determined according to the weight value corresponding to each second recommended word.
  • the weight of the second recommended word may be determined according to the user's historical on-screen messages within a preset period, the usage of the second recommended word, the user's retrieval information on the search engine, browsing information, and the like.
  • first recommended words there may also be multiple first recommended words determined according to the first scene information.
  • the default first recommended word is determined according to the weight value of the first recommended word.
  • a recommended word, and target recommendation information is generated and displayed according to the default first recommended word and the second recommended word.
  • the weight value of the first recommendation word may be determined according to the degree of matching between the second scene information corresponding to the first recommendation word and the first scene information, the user's historical screen information, and the like.
  • a trigger operation can be performed on the target recommendation information containing the default first recommendation word, and the input engine responds to the user's trigger operation and displays each first recommendation word and second recommendation word in the recommendation display area.
  • Target recommendation information generated by the combination of recommended words for users to choose.
  • FIG. 4 a presentation diagram of a first recommended word provided by an embodiment of the present application is shown.
  • the default first recommendation word is "together”
  • the target recommendation information "Let's go to eat together” containing the default first recommendation word "together” is displayed in the recommendation display area. If the user is not satisfied with the displayed target recommendation information, you can click More options corresponding to the target recommendation information "Let's go to eat together", so as to view the target recommendation information generated by the combination of each first recommendation word and second recommendation word matching the first scene information.
  • the first display order of the first recommended words is determined according to the weight value of each first recommended word , and then determine the second display order of the second recommendation word corresponding to the first recommendation word according to the weight value of each second recommendation word corresponding to the first recommendation word, and determine each first recommendation word according to the first display order and the second display order.
  • the display order of the target recommendation information generated by the combination of the recommended word and the second recommended word.
  • the user can also directly input the message content in the input box, and the input engine filters the target recommendation information according to the message content input by the user, The filtered target recommendation information is displayed in the display area, or the target information is directly generated according to the content of the message input by the user.
  • Step 206 in the case of receiving the confirmation operation for the target information, input the target information.
  • the target information In generating the target information, it is further judged whether the generated target information meets the user's requirements, and if the user's confirmation operation on the target information is received, the target information is used for input. For example, the generated target information is "I really want to eat hot pot in China Trade Plaza", but the user wants to go to other places, then the user can modify the generated target information, for example, to "I really want to eat Wanda Plaza's hot pot" "Hotpot", the target information is input only when the user's confirmation operation for the target information is received, so as to prevent the input target information from not meeting the user's expectations.
  • the method further includes: updating the recommended vocabulary corresponding to the user according to the input target information and the first scene information.
  • the user's recommended word database may also be updated according to the matching situation between the input target information and the target recommended words provided by the input engine, and the first scene information corresponding to the target information. Specifically, if the user generates the target information according to the target recommendation information, the second scene information corresponding to the first recommendation word included in the target recommendation information in the recommendation word database is updated according to the first scene information.
  • the display interface when the display interface includes an input area, the first scene information corresponding to the display interface is obtained, the first recommended word is determined according to the first scene information, and the first recommended word is determined according to the first scene information.
  • target information is generated according to the first recommendation word and the second recommendation word contained in the target recommendation information; after receiving the confirmation of the target information In the case of operation, the target information is used for input, thereby improving the efficiency and accuracy of information input.
  • the execution subject may be an information recommendation device, or a control module in the information recommendation device for executing the information recommendation method.
  • the method provided by the embodiment of the present application is described by taking the information recommending apparatus executing the information recommending method as an example.
  • FIG. 5 it shows a structural diagram of an information recommendation apparatus provided in Embodiment 3 of the present application, which specifically includes:
  • the first scene information obtaining module 301 is configured to obtain first scene information corresponding to the display interface when the display interface of the electronic device includes an input area.
  • the first scene information includes at least one item of time, location, and application program corresponding to the display interface.
  • the recommended word determination module 302 is configured to determine a first recommended word according to the first scene information, and determine a second recommended word corresponding to the first recommended word.
  • the target recommendation word output module 303 is configured to display M pieces of target recommendation information based on the first recommendation word and the second recommendation word.
  • the information recommendation apparatus in the embodiment of the present application may be an apparatus, or may be a component, an integrated circuit, or a chip in a terminal.
  • the apparatus may be a mobile electronic device or a non-mobile electronic device.
  • the mobile electronic device may be a mobile phone, a tablet computer, a notebook computer, a palmtop computer, an in-vehicle electronic device, a wearable device, an ultra-mobile personal computer (UMPC), a netbook, or a personal digital assistant (Personal Digital Assistant).
  • the electronic device can also 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. , the embodiments of the present application are not specifically limited.
  • Network Attached Storage NAS
  • PC Personal Computer
  • TV Television
  • teller machine teller machine
  • self-service machine etc.
  • the embodiments of the present application are not specifically limited.
  • the information recommendation device in the embodiment of the present application may be a device with an operating system.
  • the operating system may be an Android (Android) operating system, an ios operating system, or other possible operating systems, which are not specifically limited in the embodiments of the present application.
  • the information recommendation apparatus provided in the embodiments of the present application can implement each process implemented by the apparatus in the method embodiments of FIG. 1 to FIG. 2 , and to avoid repetition, details are not repeated here.
  • the first scene information corresponding to the display interface is obtained, the first recommended word is determined according to the first scene information, and the first recommended word is determined according to the first scene information.
  • the second recommendation word corresponding to the first recommendation word display M pieces of target recommendation information based on the first recommendation word and the second recommendation word, and the target recommendation information can be determined according to the scene information, which improves the real-time performance of information recommendation and accuracy.
  • FIG. 6 shows a structural diagram of an information recommendation apparatus provided in Embodiment 4 of the present application, which specifically includes:
  • the recommended thesaurus generating module 401 is configured to generate a recommended thesaurus corresponding to the user according to the historical on-screen information of the user and the second scene information corresponding to the historical on-screen information, and the recommended thesaurus includes pre-recommended thesaurus.
  • the preset first recommended word and the second recommended word, the preset first recommended word corresponds to the second scene information.
  • the recommended thesaurus generating module 401 includes:
  • High-frequency sentence determination sub-module 4011 configured to determine at least two high-frequency sentences of the user according to the screen-on-screen frequency of the user's historical screen-on-screen information;
  • Clustering sub-module 4012 configured to cluster the at least two high-frequency sentences according to the second scene information corresponding to the high-frequency sentences to obtain a high-frequency sentence group;
  • the first recommended word determination sub-module 4013 is configured to determine the first recommended words corresponding to the at least two high-frequency sentences according to the high-frequency sentence group and the preset similarity condition;
  • the second recommended word determination sub-module 4014 is configured to extract the second inferred word corresponding to the first recommended word in the at least two high-frequency sentences;
  • a recommended thesaurus generating sub-module 4015 is configured to generate a recommended thesaurus corresponding to the user according to the first recommended word and the second recommended word.
  • the first scene information acquisition module 402 is configured to acquire first scene information corresponding to the display interface when the display interface includes an input area, where the first scene information includes the time, place, and belonging to the display interface. At least one of the applications.
  • the recommended word determination module 403 is configured to determine a first recommended word according to the first scene information, and determine a second recommended word corresponding to the first recommended word.
  • the recommended word determination module 403 includes:
  • the recommended word determination sub-module 4031 is used to search the recommended word database for the first recommended word corresponding to the second scene information that matches the first scene information, and the first recommended word corresponding to the first recommended word. Two recommendation words.
  • the target recommendation word output module 404 is configured to display M pieces of target recommendation information based on the first recommendation word and the second recommendation word.
  • the target recommendation information output module 404 includes:
  • the default second recommended word determination sub-module 4041 is configured to determine a default second recommended word among at least two second recommended words corresponding to the first recommended word;
  • the recommended word module generation sub-module 4042 is used to combine the first recommended word and the default second recommended word to generate target recommendation information
  • the target message generating module 405 is configured to generate target information according to the target recommendation information in response to a triggering operation on the target recommendation information.
  • the target information generation module 405 includes:
  • the first target information generation sub-module 4051 is configured to generate target information according to the first recommended word and the default second recommended word in response to the confirmation operation for the target recommendation information.
  • the target information generation module 405 includes:
  • Second recommendation word display sub-module 4052 configured to display at least two second recommendation words corresponding to the first recommendation word in the target recommendation information in response to a triggering operation on the default second recommendation word in the target recommendation information word of recommendation;
  • the target second recommended word determination sub-module 4053 is configured to determine the target second recommended word in response to the selection operation on the at least two second recommended words;
  • the second target message generation sub-module 4054 is configured to generate target information according to the first recommendation word and the target second recommendation word;
  • the target information recommendation module 406 is configured to input the target information in the case of receiving the confirmation operation for the target information.
  • the device further includes:
  • the recommended thesaurus updating module 407 is configured to update the recommended thesaurus corresponding to the user according to the inputted target information and the first scene information.
  • the information recommendation device in the embodiment of the present application may be a device, or may be a component, an integrated circuit, or a chip in a terminal.
  • the apparatus may be a mobile electronic device or a non-mobile electronic device.
  • the mobile electronic device may be a mobile phone, a tablet computer, a notebook computer, a palmtop computer, an in-vehicle electronic device, a wearable device, an ultra-mobile personal computer (UMPC), a netbook, or a personal digital assistant (personal digital assistant).
  • UMPC ultra-mobile personal computer
  • netbook or a personal digital assistant
  • non-mobile electronic devices can be servers, network attached storage (Network Attached Storage, NAS), personal computer (personal computer, PC), television (television, TV), teller machine or self-service machine, etc., this application Examples are not specifically limited.
  • Network Attached Storage NAS
  • personal computer personal computer, PC
  • television television
  • teller machine or self-service machine etc.
  • the information recommendation device in the embodiment of the present application may be a device with an operating system.
  • the operating system may be an Android (Android) operating system, an ios operating system, or other possible operating systems, which are not specifically limited in the embodiments of the present application.
  • the information recommendation apparatus provided in the embodiments of the present application can implement each process implemented by the apparatus in the method embodiments of FIG. 1 to FIG. 2 , and to avoid repetition, details are not repeated here.
  • the display interface of the electronic device includes an input box
  • the first scene information corresponding to the display interface is obtained, the first recommended word is determined according to the first scene information, and the first recommended word is determined according to the first scene information.
  • an embodiment of the present application further provides an electronic device 700, including a processor 701, a memory 702, a program or instruction stored in the memory 702 and executable on the processor 701,
  • the program or instruction is executed by the processor 701
  • the operation of any one of the above-mentioned information recommendation methods is implemented, and the same technical effect can be achieved. To avoid repetition, details are not repeated here.
  • the electronic devices in the embodiments of the present application include the aforementioned mobile electronic devices and non-mobile electronic devices.
  • FIG. 8 is a schematic diagram of a hardware structure of an electronic device implementing an embodiment of the present application.
  • the electronic device 800 includes but is not limited to: a radio frequency unit 801, a network module 802, an audio output unit 803, an input unit 804, a sensor 805, a display unit 806, a user input unit 807, an interface unit 808, a memory 809, and a processor 810, etc. part.
  • the electronic device 800 may also include a power source (such as a battery) for supplying power to various components, and the power source may be logically connected to the processor 810 through a power management system, so as to manage charging, discharging, and power management through the power management system. consumption management and other functions.
  • a power source such as a battery
  • the structure of the electronic device shown in FIG. 8 does not constitute a limitation on the electronic device.
  • the electronic device may include more or less components than the one shown, or combine some components, or arrange different components, which will not be repeated here. .
  • Embodiments of the present application further provide a readable storage medium, where a program or an instruction is stored on the readable storage medium, and when the program or instruction is executed by a processor, the operation of any one of the foregoing information recommendation methods is implemented, and The same technical effect can be achieved, and in order to avoid repetition, details are not repeated here.
  • the processor is the processor in the electronic device described in the foregoing embodiments.
  • the readable storage medium include tangible (non-transitory) computer-readable storage media such as electronic circuits, semiconductor memory devices, computer read-only memory (ROM), erasable ROM (EROM), Random Access Memory (RAM), flash memory, floppy disk, CD-ROM, hard disk, magnetic disk or optical disk, etc.
  • An embodiment of the present application further provides a chip, where the chip includes a processor and a communication interface, the communication interface is coupled to the processor, and the processor is configured to run a program or an instruction to implement any one of the above information recommendation methods
  • the chip includes a processor and a communication interface
  • the communication interface is coupled to the processor
  • the processor is configured to run a program or an instruction to implement any one of the above information recommendation methods
  • the chip mentioned in the embodiments of the present application may also be referred to as a system-on-chip, a system-on-chip, a system-on-a-chip, or a system-on-a-chip, or the like.

Landscapes

  • Engineering & Computer Science (AREA)
  • Databases & Information Systems (AREA)
  • Theoretical Computer Science (AREA)
  • General Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Data Mining & Analysis (AREA)
  • Human Computer Interaction (AREA)
  • Information Retrieval, Db Structures And Fs Structures Therefor (AREA)
  • User Interface Of Digital Computer (AREA)

Abstract

本申请公开了一种信息推荐方法，属于通信技术领域。所述方法包括：在所述电子设备的显示界面包括输入区域的情况下，获取所述显示界面对应的第一场景信息，所述第一场景信息包括所述显示界面所属的应用程序、所述显示界面包含的时间信息、所述电子设备的地理位置中的至少一项；根据所述第一场景信息确定第一推荐词，以及确定与所述第一推荐词相对应的第二推荐词；基于所述第一推荐词和所述第二推荐词显示M个目标推荐信息。

Description

消息内容的输入方法、装置和电子设备
相关申请的交叉引用
本申请要求享有于2020年12月25日提交的中国专利申请202011569076.8的优先权，该申请的全部内容通过引用并入本文中。
技术领域
本申请属于通信技术领域，具体涉及一种输入方法、装置和电子设备。
背景技术
在通信领域的许多应用中，都会涉及到消息内容的输入，而用户在固定的时间段、固定的场景下，会通过相同的应用程序输入相同或相似的消息内容，例如，经常在午餐时间通过聊天软件输入“去吃饭”，在开会时间段发送“去会议室开会，时间xx，地点xx”，如果用户每天都手动输入这些相同或相似的消息内容，输入过程就会很繁琐，而且输入效率低。
针对这一现象，相关技术中的输入引擎增加了快捷短语或者常用语，用户可以在输入消息内容时，在输入引擎提供的快捷短语或者常用语中选择想要输入的内容，或者，用户可以根据实际需求手动添加常用语，并在输入消息内容时选择合适的常用语作为待输入的消息内容。
然而，相关技术中的输入引擎提供的输入方法，要么需要用户手动设置推荐信息，要么是系统提供的固定推荐信息，推荐信息的方式不够灵活，准确性差。
发明内容
本申请实施例的目的是提供一种信息推荐方法，能够解决相关技术中基于输入引擎推荐的内容不够灵活，准确性差的问题。
第一方面，本申请实施例提供了一种信息推荐方法，该方法包括：
在所述电子设备的显示界面包括输入区域的情况下，获取所述显示界面对应的第一场景信息，所述第一场景信息包括所述显示界面所属的应用程序、所 述显示界面包含的时间信息、所述电子设备的地理位置中的至少一项；
根据所述第一场景信息确定第一推荐词，以及确定与所述第一推荐词相对应的第二推荐词；
基于所述第一推荐词和所述第二推荐词显示M个目标推荐信息。
第二方面，本申请实施例提供了一种信息推荐装置，该装置包括：
第一场景信息获取模块，用于在所述电子设备的显示界面包括输入区域的情况下，获取所述显示界面对应的第一场景信息，所述第一场景信息包括所述显示界面所属的应用程序、所述显示界面包含的时间信息、所述电子设备的地理位置中的至少一项；
推荐词确定模块，用于根据所述第一场景信息确定第一推荐词，以及确定与所述第一推荐词相对应的第二推荐词；
目标推荐信息输出模块，用于基于所述第一推荐词和所述第二推荐词显示M个目标推荐信息。
第三方面，本申请实施例提供了一种电子设备，该电子设备包括处理器、存储器及存储在所述存储器上并可在所述处理器上运行的程序或指令，所述程序或指令被所述处理器执行时实现如第一方面所述的方法的步骤。
第四方面，本申请实施例提供了一种可读存储介质，所述可读存储介质上存储程序或指令，所述程序或指令被处理器执行时实现如第一方面所述的方法的步骤。
第五方面，本申请实施例提供了一种芯片，所述芯片包括处理器和通信接口，所述通信接口和所述处理器耦合，所述处理器用于运行程序或指令，实现如第一方面所述的方法。
在本申请实施例中，通过在电子设备显示界面包括输入区域的情况下，获取所述显示界面对应的第一场景信息，根据所述第一场景信息确定第一推荐词，以及确定与所述第一推荐词相对应的第二推荐词；基于所述第一推荐词和所述第二推荐词显示M个目标推荐信息，提高了信息推荐的准确率和灵活性。
附图说明
图1a是本申请实施例一提供的一种信息推荐方法的具体步骤流程图；
图1b是本申请实施例一提供的另一种信息推荐方法的具体步骤流程图；
图2是本申请实施例二提供的一种信息推荐方法的具体步骤流程图；
图3是本申请实施例二提供的一种第二推荐词的展示图；
图4是本申请实施例二提供的一种第一推荐词的展示图；
图5是本申请实施例三提供的一种信息推荐装置的结构图；
图6是本申请实施例四提供的一种信息推荐装置的结构图；
图7是本申请实施例五提供的一种电子设备的结构图；
图8是本申请实施例五提供的一种电子设备的硬件结构示意图。
具体实施方式
下面将结合本申请实施例中的附图，对本申请实施例中的技术方案进行清楚、完整地描述，显然，所描述的实施例是本申请一部分实施例，而不是全部的实施例。基于本申请中的实施例，本领域普通技术人员在没有作出创造性劳动前提下所获得的所有其他实施例，都属于本申请保护的范围。
本申请的说明书和权利要求书中的术语“第一”、“第二”等是用于区别类似的对象，而不用于描述特定的顺序或先后次序。应该理解这样使用的数据在适当情况下可以互换，以便本申请的实施例能够以除了在这里图示或描述的那些以外的顺序实施。此外，说明书以及权利要求中“和/或”表示所连接对象的至少其中之一，字符“/”，一般表示前后关联对象是一种“或”的关系。
下面结合附图，通过具体的实施例及其应用场景对本申请实施例提供的语音控制方法和语音控制装置进行详细地说明。
实施例一
参照图1a，其示出了本申请实施例一提供的一种信息推荐方法的具体步骤。
步骤101，在电子设备显示界面包括输入区域的情况下，获取所述显示界面对应的第一场景信息。
本申请实施例的信息推荐方法可应用于电子设备，所述电子设备可以为移 动终端，如手机、平板电脑、笔记本电脑、掌上电脑、车载电子设备、可穿戴设备、超级移动个人计算机(ultra-mobile personal computer，UMPC)、上网本或者个人数字助理(Personal DigitalAssistant，PDA)等，或者，所述电子设备也可以为服务器、网络附属存储器(NetworkAttached Storage，NAS)、个人计算机(Personal Computer，PC)、电视机(Television，TV)、柜员机或者自助机等非移动电子设备，本申请实施例不作具体限定，本申请实施例中以移动终端为例进行描述。
在本申请实施例中，对移动终端的显示界面进行实时检测，如果检测到移动终端的显示界面包括输入区域，说明用户需要进行信息推荐，比如词语推荐、句子推荐等，此时，获取显示界面的第一场景信息。例如，当检测到显示界面为微信聊天界面且包括聊天输入区域时，获取该微信聊天界面对应的第一场景信息，以便根据第一场景信息确定待推荐的目标推荐信息。
其中，所述第一场景信息包括所述显示界面所属的应用程序、所述显示界面包含的时间信息、所述电子设备的地理位置中的至少一项。
当检测到电子设备的显示界面包括输入区域时，电子设备可以确定该显示界面所属的应用程序，例如，确定该显示界面属于聊天软件的聊天界面，还是输入引擎的搜索界面，或者是购物软件的搜索界面，等等。对于不同的应用程序，用户经常输入的内容也不相同，因此，在本申请实施例中，可以根据显示界面所属的不同应用程序确定不同的目标推荐信息。对于不同的时间段，用户经常输入的内容也不相同，例如，在中午12点左右用户经常会输入“去哪儿吃饭”，而在周一上午用户经常会输入关于会议通知的内容，因此，在本申请实施例中，在确定显示界面包括输入区域的情况下，可以通过确定该显示界面包含的时间信息，针对不同的时间确定不同的目标推荐信息。此外，在不同的地点，用户的输入内容也会不同，例如，在公司，用户经常需要输入与工作相关的内容，在商场，用户经常输入与购物相关的内容，因此，本申请实施例可以在电子设备的显示界面包括输入区域的情况下，通过确定该电子设备的地理位置确定用户当前所处的地点，进而针对不同的地点确定不同的目标推荐信息。
步骤102，根据所述第一场景信息确定第一推荐词，以及确定与所述第一推荐词相对应的第二推荐词。
用户在某些固定的时间段，或者固定的场景下，或者在特定的应用程序中，会输入一些相同或相似的内容，例如，在每周一上午发送“去XXX会议室开会，时间XXX；地点XXX；参加人XXX，议题XXX”，在中午12点左右，通过聊天类软件输入“去XXX吃饭吧”等信息。
为了避免用户经常输入大量重复内容，提高信息推荐的准确性，本申请实施例在接收到用户授权的允许获取用户信息的权限的情况下，获取用户的历史上屏信息和所述历史上屏信息对应的第二场景信息，根据获取到的历史上屏信息和第二场景信息，生成该用户的推荐词库，推荐词库中包含预置的第一推荐词和第二推荐词，预置的第一推荐词与所述第二场景信息相对应。从而当检测到显示界面包括输入框时，可以在推荐词库中查找与显示界面对应的第一场景信息相匹配的第二场景信息对应的第一推荐词，以及与第一推荐词相对应的第二推荐词。
其中，所述第一推荐词是根据用户的历史上屏消息中出现的高频率语句以及所述高频率语句对应的第二场景信息确定的，具有相同或相似的第二场景信息的高频率语句中包含的相同或语义相近的关键词就是本申请实施例中，例如用户经常在周末下午通过聊天软件给用户发送“好想吃火锅”“好想吃烤肉”“好想吃小龙虾”等消息，那么“好想吃火锅”“好想吃烤肉”“好想吃小龙虾”就是本申请中的高频率语句，这些高频率语句具有相同的第二场景信息“周末下午、聊天软件”，提取这些高频率语句中相同或语义相近的关键词为”好想吃”，那么。“好想吃”就是该用户的一个与“周末下午、聊天软件”这一第二场景信息相对应的第一推荐词。
本申请实施例中，高频率语句中一般同时包含第一推荐词和第二推荐词，第二推荐词为与第一推荐词相对应的具体内容或选项，如前述，“火锅”、“烤肉”、“小龙虾”就是与第一推荐词“好想吃”相对应的第二推荐词。
步骤103，基于所述第一推荐词和所述第二推荐词显示M个目标推荐信息。
结合前述可知，在本申请实施例中，第一推荐词和第二推荐词是从用户的高频率语句中提取出来的，单独的第一推荐词和单独的第二推荐词并不构成完成的语句，因此，需要确定的第一推荐词和第二推荐词，按照两者之间的对应关系进行组合，生成同时包含第一推荐词和第二推荐词的目标推荐信息。
例如，当获取到用户对输入引擎的调用操作对应的第一场景信息为“周末下午，聊天软件”时，在预置的推荐词库中查找到与该第一场景信息相匹配的第二场景信息对应的第一推荐词为“好想吃”，以及该第一推荐词对应的第二推荐词有“火锅”、“烤肉”、“小龙虾”，那么，将第一推荐词“好想吃”和这些第二推荐词进行组合，生成目标推荐信息“好想吃火锅”“好想吃烤肉”“好想吃小龙虾”，在推荐展示区域显示生成的目标推荐信息，以供用户选择。
综上，在本申请实施例中，通过在显示界面包括输入区域的情况下，获取所述显示界面对应的第一场景信息，根据所述第一场景信息确定第一推荐词，以及确定与所述第一推荐词相对应的第二推荐词；基于所述第一推荐词和所述第二推荐词显示M个目标推荐信息，能够根据场景信息确定目标推荐信息，提高了确定的目标推荐信息的实时性和准确性。
在显示目标推荐信息之后，可基于目标推荐信息进行输入。参照图1b，步骤103之后还可以包括：
步骤104，响应对所述目标推荐信息的触发操作，根据所述目标推荐信息生成目标信息。
若接收到用户对显示的目标推荐信息的触发操作，则确定该目标推荐信息符合用户的实际需求，那么就可以根据该目标推荐信息中包含的第一推荐词和第二推荐词生成目标信息。例如，接收到用户对目标推荐信息“好想吃火锅”的触发操作，可以直接生成目标信息“好想吃火锅”，还可以进一步分析用户的行为习惯，根据用户的行为习惯，如常用的语气词、表情包等，对目标推荐信息进行进一步优化，生成目标信息，如“好想吃火锅呀”。还可以根据用户的当前位置，获取附近符合用户需求的商家，在生成的目标信息中包含商家信息或商家位置，例如，“好想吃中贸广场的火锅呀”。
步骤105，在接收到对所述目标信息的确认操作的情况下，以所述目标信息进行输入。
在生成目标信息中，进一步判断生成的目标信息是否符合用户需求，若接收到用户对目标信息的确认操作，则以所述目标信息进行输入。例如，生成的目标信息为“好想吃中贸广场的火锅呀”，但是用户想要到其他地点，那么用户就可以对生成的目标信息进行修改，如，修改为“好想吃万达广场的火锅呀”，只有接收到用户对目标信息的确认操作时，才输入所述目标信息，避免输入的目标信息不符合用户预期。从而提高了信息输入的效率和准确率。
需要说明的是，本申请实施例提供的信息推荐方法，执行主体可以为信息推荐装置，或者该信息推荐装置中的用于执行信息推荐方法的控制模块。本申请实施例中以信息推荐装置执行信息推荐方法为例，说明本申请实施例提供的方法。
实施例二
参照图2，其示出了本申请实施例二提供的一种信息推荐方法的具体步骤。
步骤201，根据所述用户的历史上屏信息和所述历史上屏信息对应的第二场景信息，生成所述用户对应的推荐词库，所述推荐词库中包括预置的第一推荐词和第二推荐词，所述预置的第一推荐词与所述第二场景信息相对应。
在本申请实施例中，在接收到用户授权的允许获取用户信息的权限的情况下，获取用户的历史上屏信息和所述历史上屏信息对应的第二场景信息，根据获取到的历史上屏信息和第二场景信息，生成该用户的推荐词库，推荐词库中包含预置的第一推荐词和第二推荐词，预置的第一推荐词与所述第二场景信息相对应。从而当接收到用户对输入引擎的调用操作时，可以在推荐词库中查找与调用操作对应的第一场景信息相匹配的第二场景信息对应的第一推荐词，以及与第一推荐词相对应的第二推荐词。
在本申请的一种可选实施例中，步骤201所述根据所述用户的历史上屏信息和所述历史上屏信息对应的第二场景信息，生成所述用户对应的推荐词库，包括：
步骤S11、根据所述用户的历史上屏信息的上屏频率确定所述用户的至少两个高频率语句；
步骤S12、根据所述高频率语句对应的第二场景信息对所述至少两个高频率语句进行聚类，得到高频率语句组；
步骤S13、按照所述高频率语句组和预设相似度条件确定所述至少两个高频率语句对应的第一推荐词；
步骤S14、提取所述至少两个高频率语句中与所述第一推荐词相对应的第二推词；
步骤S15、根据所述第一推荐词和所述第二推荐词生成所述用户对应的推荐词库。
需要明确的是，本申请实施例是针对用户经常在某些固定的时间段，或者固定的场景下，或者在特定的应用程序中，需要输入一些相同或相似的内容的情况下，为了提高输入引擎推荐内容的实时性和准确性，提供了一种信息推荐方法。本申请实施例中的推荐词，都是用户经常会用到的，因此，在确定该用户的推荐词库之前，需要先确定该用户使用的高频率语句。
具体的，根据用户的历史上屏信息的上屏频率，从该用户的历史上屏信息中查找至少两个上屏频率超出预设频率阈值的历史上屏信息，将所述至少两个上屏频率超出预设频率阈值的历史上屏信息作为该用户的至少两个高频率语句。每一个高频率语句对应一个第二场景信息，根据高频率语句对应的第二场景信息对至少两个高频率语句进行聚类，得到高频率语句组。例如，根据用户的历史上屏信息的上屏频率，得到该用户的高频率语句有“去会议室开会”、“好想吃火锅”、“好想吃烤肉”、“好想吃小龙虾”。其中，“去会议室开会”对应的第二场景信息为周一上午，“好想吃火锅”、“好想吃烤肉”、“好想吃小龙虾”对应的第二场景信息均包含周末下午。按照高频率语句对应的第二场景信息对这几个高频率语句进行聚类，得到两个高频率语句组，其中，“去会议室开会”属于一个高频率语句组，“好想吃火锅”、“好想吃烤肉”、“好想吃小龙虾”属于另一个高频率语句组。按照得到的高频率语句组和预设相似度条件确定第一推荐 词，并提取至少两个高频率语句中与第一关键词相对应的第二关键词。具体的，可以先对高频率语句组包含的各个高频率语句进行拆分，得到多个关键词，这些多个关键词形成所述高频率语句组对应的关键词集合，分别计算得到的关键词集合中各个关键词之间的相似度，也就是计算每两个关键词之间的相似度，将相似度超出预设相似度阈值的关键词进行合并，合并后的关键词就是该高频率语句组对应的第一推荐词，用合并后的关键词，也就是第一推荐词替换掉关键词集合中预设相似度阈值的关键词，得到更新后的关键词集合，更新后的关键词集合中，不是第一推荐词的关键词，就是该高频率语句组对应的第二推荐词。根据该高频率语句组中，第一关键词和第二关键词在高频率语句中的组合情况，确定得到的各个第一关键词和各个第二关键词的对应关系。
例如，对于“去会议室开会”所属的高频率语句组，第一关键词可以为”去会议室”，第二关键词可以为“开会”，或者，第一关键词可以为“开会”，第二关键词为“去会议室”，由于在这个高频率语句组中，只包含一个高频率语句，所以，该高频率语句组对应的第一推荐词和第二推荐词一一对应。对于“好想吃火锅”、“好想吃烤肉”、“好想吃小龙虾”所属的高频率语句组，明显相似度超出预设阈值的关键词为“好想吃”，因此，“好想吃”就是该高频率语句组的第一推荐词，那么，在各个高频率语句中，与“好想吃”组合出现的“火锅”、“烤肉”、“小龙虾”就是该第一推荐词对应的第二推荐词。
根据得到的第一推荐词和第二推荐词生成所述用户对应的推荐词库。在该用户的推荐词库中，第一推荐词与第二场景信息相对应，第二推荐词与第一推荐词相对应。
步骤202，在电子设备的显示界面包括输入区域的情况下，获取所述显示界面对应的第一场景信息。
其中，所述第一场景信息包括所述显示界面所属的应用程序、所述显示界面包含的时间信息、所述显示界面所在电子设备的地理位置中的至少一项。
该步骤可以参照步骤101，本申请实施例在此不做进一步赘述。
步骤203，在所述推荐词库中查找与所述第一场景信息相匹配的第二场景 信息对应的第一推荐词，以及与所述第一推荐词相对应的第二推荐词。
当检测到显示界面包括输入区域时，可以在推荐词库中查找与显示界面对应的第一场景信息相匹配的第二场景信息对应的第一推荐词，以及与第一推荐词相对应的第二推荐词。
例如用户经常在周末下午通过聊天软件给朋友发送“好想吃火锅”“好想吃烤肉”“好想吃小龙虾”等消息，那么“好想吃火锅”“好想吃烤肉”“好想吃小龙虾”就是本申请中的高频率语句，这些高频率语句具有相同的第二场景信息“周末下午、聊天软件”，提取这些高频率语句中相同或语义相近的关键词为”好想吃”，那么。“好想吃”就是该用户的一个与“周末下午、聊天软件”这一第二场景信息相对应的第一推荐词，“火锅”、“烤肉”、“小龙虾”就是与第一推荐词“好想吃”相对应的第二推荐词。
当获取到显示界面对应的第一场景信息为“周末下午，聊天软件”时，在预置的推荐词库中查找到与该第一场景信息相匹配的第二场景信息对应的第一推荐词为“好想吃”，以及该第一推荐词对应的第二推荐词有“火锅”、“烤肉”、“小龙虾”。
步骤204，基于所述第一推荐词和所述第二推荐词显示M个目标推荐信息。
在本申请实施例中，第一推荐词和第二推荐词是从用户的高频率语句中提取出来的，单独的第一推荐词和单独的第二推荐词并不构成完成的语句，因此，需要确定的第一推荐词和第二推荐词，按照两者之间的对应关系进行组合，生成同时包含第一推荐词和第二推荐词的目标推荐信息。
将前述步骤203确定的第一推荐词“好想吃”和第二推荐词“火锅”、“烤肉”、“小龙虾”进行组合，生成目标推荐信息“好想吃火锅”“好想吃烤肉”“好想吃小龙虾”，在推荐展示区域显示生成的目标推荐信息，以供用户选择。
在本申请的一种可选实施例中，所述第一推荐词对应的第二推荐词的个数大于1，步骤204所述对所述第一推荐词和所述第二推荐词进行组合生成目标推荐信息，包括：
步骤S21、在所述第一推荐词对应的至少两个第二推荐词中，确定默认第 二推荐词；
步骤S22、对所述第一推荐词和所述默认第二推荐词进行组合生成目标推荐信息。
具体的，当第一推荐词对应的第二推荐词的个数大于1时，根据用户在预设周期内的历史上屏消息、第二推荐词的使用情况、用户在搜索引擎上的检索信息、浏览信息等确定第二推荐词的权重，并将权重值最大的第二推荐词作为默认第二推荐词。例如，用户在一天前查看了火锅的推荐菜品及用户评价，而没有在近期浏览烤肉、小龙虾的相关信息，则在第一推荐词“好想吃”对应的第二推荐词“火锅”、“烤肉”、“小龙虾”中，“火锅”的权重值最大，将“火锅”作为默认第二推荐词，并将第一推荐词“好想吃”和默认第二推荐词“火锅”进行组合生成目标推荐信息“好想吃火锅”。
步骤205，响应对所述目标推荐信息的触发操作，根据所述目标推荐信息生成目标信息。
在本申请的一种可选实施例中，步骤205所述响应对所述目标推荐信息的触发操作，根据所述目标推荐词中包含的第一推荐词和第二推荐词生成目标信息，包括：
响应对所述目标推荐信息的确认操作，根据所述第一推荐词和所述默认第二推荐词生成目标信息。
若接收到用户对显示的目标推荐信息的确认操作，则确定该目标推荐信息符合用户的实际需求，那么就可以根据该目标推荐信息中包含的第一推荐词和第二推荐词生成目标信息。例如，接收到用户对目标推荐信息“好想吃火锅”的确认操作，可以直接生成目标信息包含第一推荐词“好想吃”和默认第二推荐词“火锅”的目标消息“好想吃火锅”，还可以进一步分析用户的行为习惯，根据用户的行为习惯，如常用的语气词、表情包等，对目标推荐信息进行进一步优化，生成目标信息，如“好想吃火锅呀”。还可以根据用户的当前位置，获取附近符合用户需求的商家，在生成的目标信息中包含商家信息或商家位置，例如，“好想吃中贸广场的火锅呀”。
在本申请的一种可选实施例中，步骤205所述响应对所述目标推荐信息的触发操作，根据所述目标推荐信息中包含的第一推荐词和第二推荐词生成目标信息，包括：
步骤S31、响应对所述目标推荐信息中的所述默认第二推荐词的触发操作，显示所述目标推荐信息中的第一推荐词对应的至少两个第二推荐词；
步骤S32、响应对所述至少两个第二推荐词的选择操作，确定目标第二推荐词；
步骤S33、根据所述第一推荐词和所述目标第二推荐词生成目标信息。
在本申请实施例中，若用户对输入引擎提供的默认第二推荐词不满意，用户可以对默认第二推荐词执行触发操作，例如，点击默认第二推荐词，输入引擎响应于用户对默认第二推荐词的触发操作，在推荐展示区域展示目标推荐信息中的第一推荐词对应的所有第二推荐词，以供用户选择。根据用户的选择操作，确定目标第二推荐词，并根据第一推荐词和目标第二推荐词生成目标信息。
参照图3，示出了本申请实施例提供的一种第二推荐词的展示图。如图2所示，假设当确定的第一推荐词为“好想吃”时，根据各个第二推荐词的权重值，确定的默认第二推荐词为“火锅”，根据第一推荐词和默认推荐词生成目标推荐信息，并显示在推荐展示区域内。若用户对提供的默认第二推荐词“火锅”不满意，则可以对默认第二推荐词执行触发操作，例如点击默认推荐词“火锅”，输入引擎就会在推荐显示区域显示第一推荐词“好想吃”对应的其他第二推荐词，例如“烤肉”、“小龙虾”、“海鲜”。第二推荐词的显示顺序是根据各个第二推荐词对应的权重值决定的。具体的，可以根据用户在预设周期内的历史上屏消息、第二推荐词的使用情况、用户在搜索引擎上的检索信息、浏览信息等确定第二推荐词的权重。
可选地，在本申请实施例中，根据第一场景信息确定的第一推荐词也可能存在多个，当第一推荐词的数目大于1时，根据第一推荐词的权重值确定默认第一推荐词，根据默认第一推荐词和第二推荐词生成目标推荐信息并显示。其中，第一推荐词的权重值可以根据第一推荐词对应的第二场景信息与第一场景 信息的匹配度、用户的历史上屏信息等确定。若用户对显示的目标推荐信息不满意，可以通过对包含默认第一推荐词的目标推荐信息执行触发操作，输入引擎响应于用户的触发操作，在推荐显示区域显示各个第一推荐词和第二推荐词组合生成的目标推荐信息，以供用户选择。
参照图4，示出了本申请实施例提供的一种第一推荐词的展示图。假设确定默认第一推荐词为“一起”，在推荐显示区域显示包含默认第一推荐词“一起”的目标推荐信息“一起去吃饭吧”，若用户对显示的目标推荐信息不满意，可以点击目标推荐信息“一起去吃饭吧”对应的更多选项，从而查看与第一场景信息相匹配的各个第一推荐词与第二推荐词组合生成的目标推荐信息。
其中，若第一场景信息对应多个第一推荐词，存在至少一个第一推荐词对应多个第二推荐词，则根据各个第一推荐词的权重值确定第一推荐词的第一显示顺序，再根据第一推荐词对应的各个第二推荐词的权重值，确定该第一推荐词对应的第二推荐词的第二显示顺序，根据第一显示顺序和第二显示顺序确定各个第一推荐词和第二推荐词组合生成的目标推荐信息的显示顺序。
可选地，在本申请实施例中，若用户对展示区域显示的目标推荐信息不满意，也可以直接在输入框内输入消息内容，输入引擎根据用户输入的消息内容对目标推荐信息进行筛选，在展示区域显示筛选后的目标推荐信息，或者，直接根据用户输入的消息内容生成目标信息。
步骤206，在接收到对所述目标信息的确认操作的情况下，以所述目标信息进行输入。
在生成目标信息中，进一步判断生成的目标信息是否符合用户需求，若接收到用户对目标信息的确认操作，则以该目标信息进行输入。例如，生成的目标信息为“好想吃中贸广场的火锅呀”，但是用户想要到其他地点，那么用户就可以对生成的目标信息进行修改，如，修改为“好想吃万达广场的火锅呀”，只有接收到用户对目标信息的确认操作时，输入所述目标信息，避免输入的目标信息不符合用户预期。
可选的，在步骤206之后，所述方法还包括：根据输入的所述目标信息以 及所述第一场景信息，更新所述用户对应的推荐词库。
在申请实施例中，还可以根据输入的目标信息和输入引擎提供的目标推荐词的匹配情况，以及该目标信息对应的第一场景信息，更新该用户的推荐词库。具体的，若用户根据目标推荐信息生成目标信息，则根据第一场景信息更新推荐词库中该目标推荐信息包含的第一推荐词对应的第二场景信息。
综上，在本申请实施例中，通过在显示界面包括输入区域的情况下，获取所述显示界面对应的第一场景信息，根据所述第一场景信息确定第一推荐词，以及确定与所述第一推荐词相对应的第二推荐词；基于所述第一推荐词和所述第二推荐词显示M个目标推荐信息；能够根据场景信息确定目标推荐信息，提高了信息推荐的准确率和实时性。
在需要进行信息输入时，响应对所述目标推荐信息的触发操作，根据所述目标推荐信息中包含的第一推荐词和第二推荐词生成目标信息；在接收到对所述目标信息的确认操作的情况下，以所述目标信息进行输入，进而提高了信息输入的效率和准确率。
需要说明的是，本申请实施例提供的信息推荐方法，执行主体可以为信息推荐装置，或者该信息推荐装置中的用于执行信息推荐方法的控制模块。本申请实施例中以信息推荐装置执行信息推荐方法为例，说明本申请实施例提供的方法。
实施例三
参照图5，其示出了本申请实施例三提供的一种信息推荐装置的结构图，具体包括：
第一场景信息获取模块301，用于在电子设备的显示界面包括输入区域的情况下，获取所述显示界面对应的第一场景信息。
其中，所述第一场景信息包括所述显示界面对应的时间、地点、所属应用程序中的至少一项。
推荐词确定模块302，用于根据所述第一场景信息确定第一推荐词，以及确定与所述第一推荐词相对应的第二推荐词。
目标推荐词输出模块303，用于基于所述第一推荐词和所述第二推荐词显示M个目标推荐信息。
本申请实施例中的信息推荐装置可以是装置，也可以是终端中的部件、集成电路、或芯片。该装置可以是移动电子设备，也可以为非移动电子设备。示例性的，移动电子设备可以为手机、平板电脑、笔记本电脑、掌上电脑、车载电子设备、可穿戴设备、超级移动个人计算机(ultra-mobile personal computer，UMPC)、上网本或者个人数字助理(Personal Digital Assistant，PDA)等，或者，所述电子设备也可以为服务器、网络附属存储器(Network Attached Storage，NAS)、个人计算机(Personal Computer，PC)、电视机(Television，TV)、柜员机或者自助机等，本申请实施例不作具体限定。
本申请实施例中的信息推荐装置可以为具有操作系统的装置。该操作系统可以为安卓(Android)操作系统，可以为ios操作系统，还可以为其他可能的操作系统，本申请实施例不作具体限定。
本申请实施例提供的信息推荐装置能够实现图1至图2的方法实施例中装置实现的各个过程，为避免重复，这里不再赘述。
在本申请实施例中，通过在电子设备的显示界面包括输入区域的情况下，获取所述显示界面对应的第一场景信息，根据所述第一场景信息确定第一推荐词，以及确定与所述第一推荐词相对应的第二推荐词；基于所述第一推荐词和所述第二推荐词显示M个目标推荐信息，能够根据场景信息确定目标推荐信息，提高了信息推荐的实时性和准确性。
实施例四
参照图6，其示出了本申请实施例四提供的一种信息推荐装置的结构图，具体包括：
推荐词库生成模块401，用于根据所述用户的历史上屏信息和所述历史上屏信息对应的第二场景信息，生成所述用户对应的推荐词库，所述推荐词库中包括预置的第一推荐词和第二推荐词，所述预置的第一推荐词与所述第二场景信息相对应。
可选地，所述推荐词库生成模块401，包括：
高频率语句确定子模块4011，用于根据所述用户的历史上屏信息的上屏频率确定所述用户的至少两个高频率语句；
聚类子模块4012，用于根据所述高频率语句对应的第二场景信息对所述至少两个高频率语句进行聚类，得到高频率语句组；
第一推荐词确定子模块4013，用于按照所述高频率语句组和预设相似度条件确定所述至少两个高频率语句对应的第一推荐词；
第二推荐词确定子模块4014，用于提取所述至少两个高频率语句中与所述第一推荐词相对应的第二推词；
推荐词库生成子模块4015，用于根据所述第一推荐词和所述第二推荐词生成所述用户对应的推荐词库。
第一场景信息获取模块402，用于在显示界面包括输入区域的情况下，获取所述显示界面对应的第一场景信息，所述第一场景信息包括所述显示界面对应的时间、地点、所属应用程序中的至少一项。
推荐词确定模块403，用于根据所述第一场景信息确定第一推荐词，以及确定与所述第一推荐词相对应的第二推荐词。
可选地，所述推荐词确定模块403，包括：
推荐词确定子模块4031，用于在所述推荐词库中查找与所述第一场景信息相匹配的第二场景信息对应的第一推荐词，以及与所述第一推荐词相对应的第二推荐词。
目标推荐词输出模块404，用于基于所述第一推荐词和所述第二推荐词显示M个目标推荐信息。
可选地，所述第一推荐词对应的第二推荐词的个数大于1，所述目标推荐信息输出模块404，包括：
默认第二推荐词确定子模块4041，用于在所述第一推荐词对应的至少两个第二推荐词中，确定默认第二推荐词；
推荐词模块生成子模块4042，用于对所述第一推荐词和所述默认第二推荐 词进行组合生成目标推荐信息；
目标消息生成模块405，用于响应对所述目标推荐信息的触发操作，根据所述目标推荐信息生成目标信息。
可选地，所述目标信息生成模块405，包括：
第一目标信息生成子模块4051，用于响应对所述目标推荐信息的确认操作，根据所述第一推荐词和所述默认第二推荐词生成目标信息。
可选地，所述目标信息生成模块405，包括：
第二推荐词显示子模块4052，用于响应对所述目标推荐信息中的所述默认第二推荐词的触发操作，显示所述目标推荐信息中的第一推荐词对应的至少两个第二推荐词；
目标第二推荐词确定子模块4053，用于响应对所述至少两个第二推荐词的选择操作，确定目标第二推荐词；
第二目标消息生成子模块4054，用于根据所述第一推荐词和所述目标第二推荐词生成目标信息；
目标信息推荐模块406，用于在接收到对所述目标信息的确认操作的情况下，以所述目标信息进行输入。
可选的，所述装置还包括：
推荐词库更新模块407，用于根据输入的所述目标信息以及所述第一场景信息，更新所述用户对应的推荐词库。
本申请实施例中的信息推荐装置可以是装置，也可以是终端中的部件、集成电路、或芯片。该装置可以是移动电子设备，也可以为非移动电子设备。示例性的，移动电子设备可以为手机、平板电脑、笔记本电脑、掌上电脑、车载电子设备、可穿戴设备、超级移动个人计算机(ultra-mobile personal computer，UMPC)、上网本或者个人数字助理(personal digital assistant，PDA)等，非移动电子设备可以为服务器、网络附属存储器(Network Attached Storage，NAS)、个人计算机(personal computer，PC)、电视机(television，TV)、柜员机或者自助机等，本申请实施例不作具体限定。
本申请实施例中的信息推荐装置可以为具有操作系统的装置。该操作系统可以为安卓(Android)操作系统，可以为ios操作系统，还可以为其他可能的操作系统，本申请实施例不作具体限定。
本申请实施例提供的信息推荐装置能够实现图1至图2的方法实施例中装置实现的各个过程，为避免重复，这里不再赘述。
在本申请实施例中，通过在电子设备的显示界面包括输入框的情况下，获取所述显示界面对应的第一场景信息，根据所述第一场景信息确定第一推荐词，以及确定与所述第一推荐词相对应的第二推荐词；基于所述第一推荐词和所述第二推荐词显示M个目标推荐信息；能够根据场景信息确定目标推荐信息，提高了确定的目标推荐信息的实时性和准确性。
实施例五
可选的，如图7所示，本申请实施例还提供一种电子设备700，包括处理器701，存储器702，存储在存储器702上并可在所述处理器701上运行的程序或指令，该程序或指令被处理器701执行时实现上述信息推荐方法的任意一种实施例的操作，且能达到相同的技术效果，为避免重复，这里不再赘述。
需要注意的是，本申请实施例中的电子设备包括上述所述的移动电子设备和非移动电子设备。
图8为实现本申请实施例的一种电子设备的硬件结构示意图。
该电子设备800包括但不限于：射频单元801、网络模块802、音频输出单元803、输入单元804、传感器805、显示单元806、用户输入单元807、接口单元808、存储器809、以及处理器810等部件。
本领域技术人员可以理解，电子设备800还可以包括给各个部件供电的电源(比如电池)，电源可以通过电源管理系统与处理器810逻辑相连，从而通过电源管理系统实现管理充电、放电、以及功耗管理等功能。图8中示出的电子设备结构并不构成对电子设备的限定，电子设备可以包括比图示更多或更少的部件，或者组合某些部件，或者不同的部件布置，在此不再赘述。
实施例六
本申请实施例还提供一种可读存储介质，所述可读存储介质上存储有程序或指令，该程序或指令被处理器执行时实现上述信息推荐方法的任意一种实施例的操作，且能达到相同的技术效果，为避免重复，这里不再赘述。
其中，所述处理器为上述实施例中所述的电子设备中的处理器。所述可读存储介质的示例包括有形(非暂态)计算机可读存储介质，如电子电路、半导体存储器设备、计算机只读存储器(Read-Only Memory，ROM)、可擦除ROM(EROM)、随机存取存储器(Random Access Memory，RAM)、闪存、软盘、CD-ROM、硬盘、磁碟或者光盘等。
实施例七
本申请实施例另提供了一种芯片，所述芯片包括处理器和通信接口，所述通信接口和所述处理器耦合，所述处理器用于运行程序或指令，实现上述信息推荐方法的任意一种实施例的操作，且能达到相同的技术效果，为避免重复，这里不再赘述。
应理解，本申请实施例提到的芯片还可以称为系统级芯片、系统芯片、芯片系统或片上系统芯片等。
需要说明的是，在本文中，术语“包括”、“包含”或者其任何其他变体意在涵盖非排他性的包含，从而使得包括一系列要素的过程、方法、物品或者装置不仅包括那些要素，而且还包括没有明确列出的其他要素，或者是还包括为这种过程、方法、物品或者装置所固有的要素。在没有更多限制的情况下，由语句“包括一个……”限定的要素，并不排除在包括该要素的过程、方法、物品或者装置中还存在另外的相同要素。此外，需要指出的是，本申请实施方式中的方法和装置的范围不限按示出或讨论的顺序来执行功能，还可包括根据所涉及的功能按基本同时的方式或按相反的顺序来执行功能，例如，可以按不同于所描述的次序来执行所描述的方法，并且还可以添加、省去、或组合各种步骤。另外，参照某些示例所描述的特征可在其他示例中被组合。
通过以上的实施方式的描述，本领域的技术人员可以清楚地了解到上述实施例方法可借助软件加必需的通用硬件平台的方式来实现，当然也可以通过硬 件，但很多情况下前者是更佳的实施方式。基于这样的理解，本申请的技术方案本质上或者说对相关技术做出贡献的部分可以以软件产品的形式体现出来，该计算机软件产品存储在一个存储介质(如ROM/RAM、磁碟、光盘)中，包括若干指令用以使得一台终端(可以是手机，计算机，服务器，空调器，或者网络设备等)执行本申请各个实施例所述的方法。
上面结合附图对本申请的实施例进行了描述，但是本申请并不局限于上述的具体实施方式，上述的具体实施方式仅仅是示意性的，而不是限制性的，本领域的普通技术人员在本申请的启示下，在不脱离本申请宗旨和权利要求所保护的范围情况下，还可做出很多形式，均属于本申请的保护之内。

Claims (17)

  1. 一种信息推荐方法，应用于电子设备，所述方法包括：
    在所述电子设备的显示界面包括输入区域的情况下，获取所述显示界面对应的第一场景信息，所述第一场景信息包括所述显示界面所属的应用程序、所述显示界面包含的时间信息、所述电子设备的地理位置中的至少一项；
    根据所述第一场景信息确定第一推荐词，以及确定与所述第一推荐词相对应的第二推荐词；
    基于所述第一推荐词和所述第二推荐词显示M个目标推荐信息。
  2. 根据权利要求1所述的方法，其中，所述根据所述第一场景信息确定第一推荐词，以及确定与所述第一推荐词相对应的第二推荐词之前，所述方法还包括：
    根据所述用户的历史上屏信息和所述历史上屏信息对应的第二场景信息，生成所述用户对应的推荐词库，所述推荐词库中包括预置的第一推荐词和第二推荐词，所述预置的第一推荐词与所述第二场景信息相对应；
    所述根据所述第一场景信息确定第一推荐词，以及确定与所述第一推荐词相对应的第二推荐词，包括：
    在所述推荐词库中查找与所述第一场景信息相匹配的第二场景信息对应的第一推荐词，以及与所述第一推荐词相对应的第二推荐词。
  3. 根据权利要求2所述的方法，其中，所述根据所述用户的历史上屏信息和所述历史上屏信息对应的第二场景信息，生成所述用户对应的推荐词库，包括：
    根据所述用户的历史上屏信息的上屏频率确定所述用户的至少两个高频率语句；
    根据所述高频率语句对应的第二场景信息对所述至少两个高频率语句进行聚类，得到高频率语句组；
    按照所述高频率语句组和预设相似度条件确定所述至少两个高频率语句 对应的第一推荐词；
    提取所述至少两个高频率语句中与所述第一推荐词相对应的第二推词；
    根据所述第一推荐词和所述第二推荐词生成所述用户对应的推荐词库。
  4. 根据权利要求1所述的方法，其中，所述第一推荐词对应的第二推荐词的个数大于1，所述对所述第一推荐词和所述第二推荐词进行组合生成目标推荐信息，包括：
    在所述第一推荐词对应的至少两个第二推荐词中，确定默认第二推荐词；
    基于所述第一推荐词和所述默认第二推荐词显示M个目标推荐信息。
  5. 根据权利要求4所述的方法，其中，所述基于所述第一推荐词和所述第二推荐词显示M个目标推荐信息之后，还包括：
    响应对所述目标推荐信息的触发操作，根据所述目标推荐信息生成目标消息。
  6. 根据权利要求5所述的方法，其中，所述响应对所述目标推荐信息的触发操作，根据所述目标推荐信息生成目标消息，包括：
    响应对所述目标推荐信息中的所述默认第二推荐词的触发操作，显示所述目标推荐信息中的第一推荐词对应的至少两个第二推荐词；
    响应对所述至少两个第二推荐词的选择操作，确定目标第二推荐词；
    根据所述第一推荐词和所述目标第二推荐词生成目标信息。
  7. 一种信息推荐装置，应用于电子设备，其中，所述装置包括：
    第一场景信息获取模块，用于在所述电子设备的显示界面包括输入区域的情况下，获取所述显示界面对应的第一场景信息，所述第一场景信息包括所述显示界面所属的应用程序、所述显示界面包含的时间信息、所述电子设备的地理位置中的至少一项；
    推荐词确定模块，用于根据所述第一场景信息确定第一推荐词，以及确定与所述第一推荐词相对应的第二推荐词；
    目标推荐信息输出模块，用于基于所述第一推荐词和所述第二推荐词显示M个目标推荐信息。
  8. 根据权利要求7所述的装置，其中，所述装置还包括：
    推荐词库生成模块，用于根据所述用户的历史上屏信息和所述历史上屏信息对应的第二场景信息，生成所述用户对应的推荐词库，所述推荐词库中包括预置的第一推荐词和第二推荐词，所述预置的第一推荐词与所述第二场景信息相对应；
    所述推荐词确定模块，包括：
    推荐词确定子模块，用于在所述推荐词库中查找与所述第一场景信息相匹配的第二场景信息对应的第一推荐词，以及与所述第一推荐词相对应的第二推荐词。
  9. 根据权利要求8所述的装置，其中，所述推荐词库生成模块，包括：
    高频率语句确定子模块，用于根据所述用户的历史上屏信息的上屏频率确定所述用户的至少两个高频率语句；
    聚类子模块，用于根据所述高频率语句对应的第二场景信息对所述至少两个高频率语句进行聚类，得到高频率语句组；
    第一推荐词确定子模块，用于按照所述高频率语句组和预设相似度条件确定所述至少两个高频率语句对应的第一推荐词；
    第二推荐词确定子模块，用于提取所述至少两个高频率语句中与所述第一推荐词相对应的第二推词；
    推荐词库生成子模块，用于根据所述第一推荐词和所述第二推荐词生成所述用户对应的推荐词库。
  10. 根据权利要求7所述的装置，其中，所述第一推荐词对应的第二推荐词的个数大于1，所述目标推荐信息输出模块，包括：
    默认第二推荐词确定子模块，用于在所述第一推荐词对应的至少两个第二推荐词中，确定默认第二推荐词；
    推荐词模块生成子模块，用于基于所述第一推荐词和所述默认第二推荐词显示M个目标推荐信息。
  11. 根据权利要求10所述的装置，其中，所述装置，还包括：
    目标消息生成模块，用于响应对所述目标推荐信息的确认操作，根据所述目标推荐信息生成目标消息。
  12. 根据权利要求10所述的装置，其中，所述目标消息生成模块，包括：
    第二推荐词显示子模块，用于响应对所述目标推荐信息中的所述默认第二推荐词的触发操作，显示所述目标推荐信息中的第一推荐词对应的至少两个第二推荐词；
    目标第二推荐词确定子模块，用于响应对所述至少两个第二推荐词的选择操作，确定目标第二推荐词；
    第二目标消息生成子模块，用于根据所述第一推荐词和所述目标第二推荐词生成目标信息。
  13. 一种电子设备，包括处理器，存储器及存储在所述存储器上并可在所述处理器上运行的程序或指令，所述程序或指令被所述处理器执行时实现如权利要求1至6任一所述的信息推荐方法的步骤。
  14. 一种可读存储介质，所述可读存储介质上存储程序或指令，所述程序或指令被处理器执行时实现如权利要求1至6任一所述的信息推荐方法的步骤。
  15. 一种芯片，包括处理器和通信接口，所述通信接口和所述处理器耦合，所述处理器用于运行程序或指令，实现如权利要求1至6任一项所述的信息推荐方法的步骤。
  16. 一种计算机程序产品，所述计算机程序产品被存储在非易失的存储介质中，所述程序产品被至少一个处理器执行以实现如权利要求1至6任一项所述的信息推荐方法的步骤。
  17. 一种信息推荐设备，所述信息推荐设备被配置成用于执行如权利要求1至6任一项所述的信息推荐方法的步骤。
PCT/CN2021/139657 2020-12-25 2021-12-20 消息内容的输入方法、装置和电子设备 Ceased WO2022135339A1 (zh)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
CN202011569076.8 2020-12-25
CN202011569076.8A CN112596617B (zh) 2020-12-25 2020-12-25 消息内容的输入方法、装置和电子设备

Publications (1)

Publication Number Publication Date
WO2022135339A1 true WO2022135339A1 (zh) 2022-06-30

Family

ID=75202567

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/CN2021/139657 Ceased WO2022135339A1 (zh) 2020-12-25 2021-12-20 消息内容的输入方法、装置和电子设备

Country Status (2)

Country Link
CN (1) CN112596617B (zh)
WO (1) WO2022135339A1 (zh)

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN117540057A (zh) * 2024-01-10 2024-02-09 广东省电信规划设计院有限公司 基于aigc的检索引导方法及装置

Families Citing this family (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN112596617B (zh) * 2020-12-25 2025-06-03 维沃移动通信有限公司 消息内容的输入方法、装置和电子设备
CN113128183B (zh) * 2021-04-21 2025-05-23 南京维沃软件技术有限公司 输入内容处理方法、装置、电子设备和存储介质

Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN106406565A (zh) * 2016-09-29 2017-02-15 维沃移动通信有限公司 一种移动终端词汇输入方法及移动终端
CN109582866A (zh) * 2018-11-23 2019-04-05 北京字节跳动网络技术有限公司 个性化推荐词的显示方法、装置、存储介质及电子设备
US20200257377A1 (en) * 2019-02-11 2020-08-13 Samsung Electronics Co., Ltd. Electronic device and method for recommending word in same
CN111737574A (zh) * 2020-06-19 2020-10-02 口口相传(北京)网络技术有限公司 搜索信息获取方法、装置、计算机设备及可读存储介质
CN112596617A (zh) * 2020-12-25 2021-04-02 维沃移动通信有限公司 消息内容的输入方法、装置和电子设备

Family Cites Families (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN107871259A (zh) * 2016-09-26 2018-04-03 阿里巴巴集团控股有限公司 一种信息推荐的处理方法、装置及客户端
CN110532351B (zh) * 2019-07-19 2022-04-12 口口相传(北京)网络技术有限公司 推荐词展示方法、装置、设备及计算机可读存储介质
CN111125344B (zh) * 2019-12-23 2023-09-05 新方正控股发展有限责任公司 相关词推荐方法和装置

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN106406565A (zh) * 2016-09-29 2017-02-15 维沃移动通信有限公司 一种移动终端词汇输入方法及移动终端
CN109582866A (zh) * 2018-11-23 2019-04-05 北京字节跳动网络技术有限公司 个性化推荐词的显示方法、装置、存储介质及电子设备
US20200257377A1 (en) * 2019-02-11 2020-08-13 Samsung Electronics Co., Ltd. Electronic device and method for recommending word in same
CN111737574A (zh) * 2020-06-19 2020-10-02 口口相传(北京)网络技术有限公司 搜索信息获取方法、装置、计算机设备及可读存储介质
CN112596617A (zh) * 2020-12-25 2021-04-02 维沃移动通信有限公司 消息内容的输入方法、装置和电子设备

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN117540057A (zh) * 2024-01-10 2024-02-09 广东省电信规划设计院有限公司 基于aigc的检索引导方法及装置
CN117540057B (zh) * 2024-01-10 2024-04-30 广东省电信规划设计院有限公司 基于aigc的检索引导方法及装置

Also Published As

Publication number Publication date
CN112596617B (zh) 2025-06-03
CN112596617A (zh) 2021-04-02

Similar Documents

Publication Publication Date Title
TWI492075B (zh) 在對話期間提供建議的方法，使用所述方法的電子裝置，以及電腦程式產品
US20200356572A1 (en) Search ranking method and apparatus, electronic device and storage medium
CN108541310B9 (zh) 一种显示候选词的方法、装置及图形用户界面
CN107621886B (zh) 一种输入推荐方法、装置及电子设备
US20140040741A1 (en) Smart Auto-Completion
WO2022135339A1 (zh) 消息内容的输入方法、装置和电子设备
CN107315487B (zh) 一种输入处理方法、装置及电子设备
CN109918565B (zh) 一种搜索数据的处理方法、装置及电子设备
CN108874827B (zh) 一种搜索方法及相关装置
CN109977293B (zh) 一种搜索结果相关性的计算方法及装置
CN108073303A (zh) 一种输入方法、装置及电子设备
US9009031B2 (en) Analyzing a category of a candidate phrase to update from a server if a phrase category is not in a phrase database
CN110110207A (zh) 一种信息推荐方法、装置及电子设备
CN112084151A (zh) 文件处理方法、装置和电子设备
CN107436896B (zh) 一种输入推荐方法、装置及电子设备
WO2022143524A1 (zh) 信息显示方法、装置和电子设备
CN112307281A (zh) 一种实体推荐方法及装置
WO2019165902A1 (zh) 生成、展示数据对象信息的方法及装置
CN106993085A (zh) 定位结果显示方法及装置、电子设备
US20150154682A1 (en) Enriching product catalog with search keywords
CN110633391A (zh) 一种信息搜索方法及装置
CN110147426B (zh) 一种查询文本的分类标签确定方法及相关装置
CN109901726B (zh) 一种候选词生成方法、装置及用于候选词生成的装置
CN114443951A (zh) 商品搜索方法及电子设备
CN110033338A (zh) 推荐方法和装置、用于推荐的装置

Legal Events

Date Code Title Description
121 Ep: the epo has been informed by wipo that ep was designated in this application

Ref document number: 21909335

Country of ref document: EP

Kind code of ref document: A1

NENP Non-entry into the national phase

Ref country code: DE

122 Ep: pct application non-entry in european phase

Ref document number: 21909335

Country of ref document: EP

Kind code of ref document: A1