CN112596617A - Message content input method and device and electronic equipment - Google Patents
Message content input method and device and electronic equipment Download PDFInfo
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- 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
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- G06F16/9537—Spatial or temporal dependent retrieval, e.g. spatiotemporal queries
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Abstract
The application discloses an information recommendation method, and belongs to the technical field of communication. The method comprises the following steps: under the condition that a display interface of the electronic equipment comprises an input area, acquiring first scene information corresponding to the display interface, wherein the first scene information comprises at least one of an application program to which the display interface belongs, time information contained in the display interface and a geographic position of the electronic equipment; determining a first recommended word according to the first scene information, and determining a second recommended word corresponding to the first recommended word; and displaying M pieces of target recommendation information based on the first recommendation words and the second recommendation words. According to the method and the device, the target recommendation information is determined according to the operation information corresponding to the calling operation of the user to the input engine, so that the accuracy and flexibility of information recommendation are improved.
Description
Technical Field
The application belongs to the technical field of communication, and particularly relates to an input method, an input device and electronic equipment.
Background
In many applications in the field of communications, the input of message content is involved, and a user inputs the same or similar message content through the same application program in a fixed time period and a fixed scene, for example, often inputs "go to eat" through chat software in lunch time, sends "go to a meeting room in a meeting, time xx, and place xx" in a meeting time period, and if the user manually inputs the same or similar message content every day, the input process is cumbersome and inefficient.
Aiming at the phenomenon, the existing input engine is added with shortcut phrases or commonly used phrases, when a user inputs message contents, the user can select contents to be input from the shortcut phrases or commonly used phrases provided by the input engine, or the user can manually add commonly used phrases according to actual requirements and select proper commonly used phrases as the message contents to be input when inputting the message contents.
However, the input method provided by the existing input engine either requires the user to manually set the recommendation information or is fixed recommendation information provided by the system, and the recommendation information mode is not flexible enough and has poor accuracy.
Content of application
The embodiment of the application aims to provide an information recommendation method, which can solve the problems that in the prior art, recommended contents based on an input engine are not flexible enough and are poor in accuracy.
In order to solve the technical problem, the present application is implemented as follows:
in a first aspect, an embodiment of the present application provides an information recommendation method, where the method includes:
under the condition that a display interface of the electronic equipment comprises an input area, acquiring first scene information corresponding to the display interface, wherein the first scene information comprises at least one of an application program to which the display interface belongs, time information contained in the display interface and a geographic position of the electronic equipment;
determining a first recommended word according to the first scene information, and determining a second recommended word corresponding to the first recommended word;
and displaying M pieces of target recommendation information based on the first recommendation words and the second recommendation words.
In a second aspect, an embodiment of the present application provides an information recommendation apparatus, including:
the electronic equipment comprises a first scene information acquisition module, a second scene information acquisition module and a display interface acquisition module, wherein the first scene information acquisition module is used for acquiring first scene information corresponding to a display interface of the electronic equipment under the condition that the display interface comprises an input area, and the first scene information comprises at least one of an application program of the display interface, time information contained in the display interface and a geographic position of the electronic equipment;
the recommended word determining module is used for determining a first recommended word according to the first scene information and determining a second recommended word corresponding to the first recommended word;
and the target recommendation information output module is used for displaying M pieces of target recommendation information based on the first recommendation words and the second recommendation words.
In a third aspect, an embodiment of the present application provides an electronic device, which includes a processor, a memory, and a program or instructions stored on the memory and executable on the processor, and when executed by the processor, the program or instructions implement the steps of the method according to the first aspect.
In a fourth aspect, embodiments of the present application provide a readable storage medium, on which a program or instructions are stored, which when executed by a processor implement the steps of the method according to the first aspect.
In a fifth aspect, an embodiment of the present application provides a chip, where the chip includes a processor and a communication interface, where the communication interface is coupled to the processor, and the processor is configured to execute a program or instructions to implement the method according to the first aspect.
In the embodiment of the application, under the condition that a display interface of electronic equipment comprises an input area, first scene information corresponding to the display interface is obtained, a first recommended word is determined according to the first scene information, and a second recommended word corresponding to the first recommended word is determined; and M pieces of target recommendation information are displayed based on the first recommendation words and the second recommendation words, so that the accuracy and flexibility of information recommendation are improved.
Drawings
Fig. 1a is a flowchart illustrating specific steps of an information recommendation method according to an embodiment of the present application;
FIG. 1b is a flowchart illustrating specific steps of another information recommendation method according to an embodiment of the present application;
fig. 2 is a flowchart illustrating specific steps of an information recommendation method according to a second embodiment of the present application;
FIG. 3 is a diagram illustrating a second recommended word according to a second embodiment of the present application;
FIG. 4 is a diagram illustrating a first recommended word according to a second embodiment of the present application;
fig. 5 is a structural diagram of an information recommendation device according to a third embodiment of the present application;
fig. 6 is a structural diagram of an information recommendation apparatus according to a fourth embodiment of the present application;
fig. 7 is a structural diagram of an electronic device according to a fifth embodiment of the present application;
fig. 8 is a schematic hardware structure diagram of an electronic device according to a fifth embodiment of the present application.
Detailed Description
The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are some, but not all, embodiments of the present application. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
The terms first, second and the like in the description and in the claims of the present application are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used is interchangeable under appropriate circumstances such that the embodiments of the application are capable of operation in sequences other than those illustrated or described herein. In addition, "and/or" in the specification and claims means at least one of connected objects, a character "/" generally means that a preceding and succeeding related objects are in an "or" relationship.
The following describes in detail a voice control method and a voice control apparatus provided in the embodiments of the present application with reference to the accompanying drawings through specific embodiments and application scenarios thereof.
Example one
Referring to fig. 1a, specific steps of an information recommendation method provided in an embodiment of the present application are shown.
The information recommendation method in the embodiment of the application may be applied to an electronic device, where the electronic device may be a mobile terminal, such as a mobile phone, a tablet Computer, a notebook Computer, a palm Computer, a vehicle-mounted electronic device, a wearable device, an ultra-mobile Personal Computer (UMPC), a netbook, a Personal Digital Assistant (PDA), or the like, or the electronic device may also be a non-mobile electronic device such as a server, a Network Attached Storage (NAS), a Personal Computer (PC), a Television (Television, TV), a teller machine, or a self-service machine, and the embodiment of the application is not particularly limited, and the embodiment of the application describes the electronic device by taking the mobile terminal as an example.
In the embodiment of the application, the display interface of the mobile terminal is detected in real time, and if the display interface of the mobile terminal is detected to include an input area, it is indicated that a user needs to perform information recommendation, such as word recommendation, sentence recommendation and the like, at this time, first scene information of the display interface is acquired. For example, when the display interface is detected to be a WeChat chat interface and comprises a chat input area, first scene information corresponding to the WeChat chat interface is acquired, so that target recommendation information to be recommended is determined according to the first scene information.
The first scene information comprises at least one of an application program to which the display interface belongs, time information contained in the display interface and a geographic position of the electronic equipment.
When it is detected that the display interface of the electronic device includes the input area, the electronic device may determine an application program to which the display interface belongs, for example, whether the display interface belongs to a chat interface of chat software, a search interface of an input engine, a search interface of shopping software, or the like. For different applications, the contents frequently input by the user are different, and therefore, in the embodiment of the application, different target recommendation information can be determined according to the different applications to which the display interfaces belong. For different time periods, the contents frequently input by the user are different, for example, the user often inputs "eat at home" at around 12 pm, and the user often inputs the contents related to the meeting notification in monday morning, so in the embodiment of the present application, in the case that the display interface is determined to include the input area, different target recommendation information can be determined for different times by determining the time information included in the display interface. In addition, the input content of the user may also be different at different places, for example, in a company, the user often needs to input content related to work, in a shopping mall, the user often inputs content related to shopping, and therefore, in the case that the display interface of the electronic device includes an input area, the present embodiment may determine the place where the user is currently located by determining the geographic location of the electronic device, and further determine different target recommendation information for different places.
The user may enter some of the same or similar content during some fixed time period, or under fixed scenes, or in a particular application, for example, every monday morning send "go to XXX conference room for meeting, time XXX; location XXX; participant XXX, subject XXX ", at around 12 am, enters information such as" go to XXX dining bar "through chat software.
In order to avoid that a user inputs a large amount of repeated content frequently and improve the accuracy of information recommendation, in the embodiment of the application, under the condition that the permission of obtaining user information authorized by the user is received, historical screen information of the user and second scene information corresponding to the historical screen information are obtained, a recommendation word bank of the user is generated according to the obtained historical screen information and the second scene information, the recommendation word bank comprises preset first recommendation words and second recommendation words, and the preset first recommendation words correspond to the second scene information. Therefore, when the display interface is detected to comprise the input box, the first recommended word corresponding to the second scene information matched with the first scene information corresponding to the display interface and the second recommended word corresponding to the first recommended word can be searched in the recommended word bank.
The first recommended words are determined according to high-frequency sentences appearing in historical on-screen messages of a user and second scene information corresponding to the high-frequency sentences, and the same or semantically similar keywords contained in the high-frequency sentences with the same or similar second scene information are the same keywords in the embodiment of the application. The 'good desire to eat' is a first recommended word of the user corresponding to the second scene information of 'weekend afternoon, chat software'.
In the embodiment of the present application, the high frequency sentence generally includes the first recommended word and the second recommended word at the same time, and the second recommended word is the specific content or option corresponding to the first recommended word, such as the aforementioned "hot pot", "barbecue", "crawfish" and the like, which are the second recommended words corresponding to the first recommended word "good to eat".
And 103, displaying M pieces of target recommendation information based on the first recommendation words and the second recommendation words.
In combination with the foregoing, in the embodiment of the present application, the first recommended word and the second recommended word are extracted from a high-frequency sentence of a user, and the single first recommended word and the single second recommended word do not form a complete sentence, so that the first recommended word and the second recommended word that need to be determined are combined according to a correspondence relationship between the first recommended word and the second recommended word, and target recommendation information that includes the first recommended word and the second recommended word at the same time is generated.
For example, when the first scene information corresponding to the calling operation of the user on the input engine is acquired as "weekend afternoon and chat software", the first recommended word corresponding to the second scene information matched with the first scene information is found in a preset recommended word bank as "good to eat", and the second recommended word corresponding to the first recommended word comprises "hot pot", "barbecue" and "cray", then the first recommended word "good to eat" and the second recommended words are combined to generate target recommended information of "good to eat hot pot", "good to eat barbecue" and "good to eat cray", and the generated target recommended information is displayed in a recommendation display area for the user to select.
In summary, in the embodiment of the present application, under the condition that a display interface includes an input area, first scene information corresponding to the display interface is obtained, a first recommended word is determined according to the first scene information, and a second recommended word corresponding to the first recommended word is determined; the M pieces of target recommendation information are displayed based on the first recommendation words and the second recommendation words, the target recommendation information can be determined according to scene information, and the real-time performance and the accuracy of the determined target recommendation information are improved.
After the target recommendation information is displayed, an input may be made based on the target recommendation information. Referring to fig. 1b, step 103 may further include:
and 104, responding to the trigger operation of the target recommendation information, and generating target information according to the target recommendation information.
If the triggering operation of the user on the displayed target recommendation information is received, the target recommendation information is determined to meet the actual requirement of the user, and then the target information can be generated according to the first recommendation words and the second recommendation words contained in the target recommendation information. For example, the target information 'good desire to eat hot pot' can be directly generated by receiving the trigger operation of the target recommendation information 'good desire to eat hot pot' by the user, the behavior habit of the user can be further analyzed, and the target recommendation information is further optimized according to the behavior habit of the user, such as common language words, expression packets and the like, so as to generate the target information, such as 'good desire to eat hot pot'. And nearby merchants meeting the requirements of the user can be obtained according to the current position of the user, and the generated target information contains merchant information or merchant positions, such as 'wok of a trade square in good thinking of eating'.
And 105, inputting the target information when the confirmation operation of the target information is received.
In the generation of the target information, whether the generated target information meets the requirements of the user is further judged, and if the confirmation operation of the user on the target information is received, the target information is input. For example, the generated target information is 'good desire to eat chafing dish of a Chinese product square', but the user wants to go to other places, the user can modify the generated target information, for example, the user modifies 'good desire to eat chafing dish of a Wanda square', and only receives the confirmation operation of the user on the target information, the target information is input, and the input target information is prevented from being not in accordance with the expectation of the user. Thereby improving the efficiency and accuracy of information input.
It should be noted that, in the information recommendation method provided in the embodiment of the present application, 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 an example in which an information recommendation apparatus executes an information recommendation method.
Example two
Referring to fig. 2, specific steps of an information recommendation method provided in the second embodiment of the present application are shown.
In the embodiment of the application, under the condition that the authority of a user for allowing the user information to be obtained is received, the historical screen information of the user and second scene information corresponding to the historical screen information are obtained, a recommended word bank of the user is generated according to the obtained historical screen information and the second scene information, the recommended word bank comprises preset first recommended words and second recommended words, and the preset first recommended words correspond to the second scene information. Therefore, when the calling operation of the user to the input engine is received, the first recommended word corresponding to the second scene information matched with the first scene information corresponding to the calling operation and the second recommended word corresponding to the first recommended word can be searched in the recommended word bank.
In an optional embodiment of the present application, the generating, according to the historical screen information of the user and the second scenario information corresponding to the historical screen information in step 201, a recommended word bank corresponding to the user includes:
and step S11, determining at least two high-frequency sentences of the user according to the screen-loading frequency of the historical screen-loading information of the user.
And 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.
And step S13, determining the first recommended words corresponding to the at least two high-frequency sentences according to the high-frequency sentence group and a preset similarity condition.
And step S14, extracting a second word-pushing word corresponding to the first recommended word in the at least two high-frequency sentences.
And step S15, generating a recommended word bank corresponding to the user according to the first recommended word and the second recommended word.
It should be clear that, the embodiment of the present application provides an information recommendation method for improving the real-time performance and accuracy of recommending contents by an input engine in a case that a user often needs to input some same or similar contents in a certain fixed time period, a fixed scene, or in a specific application program. The recommended words in the embodiment of the application are all commonly used by the user, so that before determining the recommended word bank of the user, the high-frequency sentences used by the user need to be determined.
Specifically, according to the screen-loading frequency of the historical screen-loading information of the user, searching at least two pieces of historical screen-loading information of which the screen-loading frequency exceeds a preset frequency threshold from the historical screen-loading information of the user, and taking the historical screen-loading information of which the screen-loading frequency exceeds the preset frequency threshold as at least two high-frequency statements of the user. And each high-frequency statement corresponds to one piece of second scene information, and at least two high-frequency statements are clustered according to the second scene information corresponding to the high-frequency statements to obtain a high-frequency statement group. For example, according to the screen-on frequency of the historical screen-on information of the user, the high-frequency sentences of the user include "going to a meeting room for meeting", "wanting to eat a hot pot", "wanting to eat a roast meat", and "wanting to eat a crayfish". The second scene information corresponding to the 'meeting room going' is Monday morning, and the second scene information corresponding to the 'good desire to eat chafing dish', 'good desire to eat barbecue' and 'good desire to eat crayfish' all comprise weekend afternoon. Clustering the high-frequency sentences according to second scene information corresponding to the high-frequency sentences to obtain two high-frequency sentence groups, wherein the 'meeting room going' belongs to one high-frequency sentence group, and the 'good desire to eat hot pot', 'good desire to eat barbecue' and 'good desire to eat crayfish' belong to the other high-frequency sentence group. And determining a first recommended word according to the obtained high-frequency sentence group and a preset similarity condition, and extracting a second keyword corresponding to the first keyword from at least two high-frequency sentences. Specifically, each high-frequency sentence included in the high-frequency sentence group may be split to obtain a plurality of keywords, the plurality of keywords form a keyword set corresponding to the high-frequency sentence group, the similarity between the keywords in the obtained keyword set is calculated respectively, that is, the similarity between every two keywords is calculated, the keywords with the similarity exceeding a preset similarity threshold are merged, the merged keyword is a first recommended word corresponding to the high-frequency sentence group, the merged keyword is used to replace the keyword with the first recommended word, which is the preset similarity threshold in the keyword set, so as to obtain an updated keyword set, and in the updated keyword set, either the keyword of the first recommended word is a second recommended word corresponding to the high-frequency sentence group. And determining the corresponding relation of each obtained first keyword and each obtained second keyword according to the combination condition of the first keyword and the second keyword in the high-frequency sentence group in the high-frequency sentence.
For example, for a high-frequency sentence group to which "meeting room for meeting" belongs, the first keyword may be "meeting room for going, and the second keyword may be" meeting ", or the first keyword may be" meeting ", and the second keyword is" meeting room for going, since only one high-frequency sentence is included in this high-frequency sentence group, the first recommended word and the second recommended word corresponding to the high-frequency sentence group are in one-to-one correspondence. For the high-frequency sentence groups to which the 'good desire to eat hot pot', 'good desire to eat roast' and 'good desire to eat crayfish' belong, the keyword with obvious similarity exceeding a preset threshold value is 'good desire to eat', so that the 'good desire to eat' is the first recommended word of the high-frequency sentence group, and then in each high-frequency sentence, the 'hot pot', 'roast' and 'crayfish' combined with the 'good desire to eat' are the second recommended words corresponding to the first recommended word.
And generating a recommended word bank corresponding to the user according to the obtained first recommended word and the second recommended word. In the word recommending library of the user, the first recommending words correspond to the second scene information, and the second recommending words correspond to the first recommending words.
The first scene information comprises at least one of an application program to which the display interface belongs, time information contained in the display interface and a geographic position of the electronic equipment in which the display interface is located.
This step may refer to step 101, and is not further described herein in this embodiment of the present application.
When the display interface is detected to comprise the input area, a first recommended word corresponding to second scene information matched with the first scene information corresponding to the display interface and a second recommended word corresponding to the first recommended word can be searched in the recommended word bank.
For example, a user often sends messages such as 'wanting to eat a hot pot', 'wanting to eat a barbecue', 'wanting to eat a crayfish' to friends through chatting software in the afternoon on weekends, the 'wanting to eat a hot pot', 'wanting to eat a barbecue', 'wanting to eat a crayfish' and the like, so that the 'wanting to eat a hot pot', 'wanting to eat a barbecue', 'wanting to eat a crayfish' are high-frequency sentences in the application, the high-frequency sentences have the same second scene information 'afternoon on weekends and chatting software', and keywords which are the same or similar in semantics in the high. The 'good desire to eat' is a first recommended word of the user corresponding to the second scene information of 'weekend afternoon and chat software', and the 'hot pot', 'barbecue' and 'crayfish' are second recommended words corresponding to the first recommended word 'good desire to eat'.
When the first scene information corresponding to the display interface is acquired as 'weekend afternoon, chat software', a first recommended word corresponding to second scene information matched with the first scene information is found in a preset recommended word bank to be 'good to eat', and a second recommended word corresponding to the first recommended word comprises 'hot pot', 'barbecue' and 'crawfish'.
And 204, displaying M pieces of target recommendation information based on the first recommendation words and the second recommendation words.
In the embodiment of the application, the first recommended word and the second recommended word are extracted from a high-frequency sentence of a user, and the single first recommended word and the single second recommended word do not form a completed sentence, so that the first recommended word and the second recommended word to be determined are combined according to the corresponding relationship between the first recommended word and the second recommended word, and target recommendation information simultaneously containing the first recommended word and the second recommended word is generated.
Combining the first recommended word "good want to eat" and the second recommended word "hot pot", "roast" and "crawfish" determined in the step 203 to generate target recommended information "good want to eat hot pot", "good want to eat roast" and "good want to eat crawfish", and displaying the generated target recommended information in a recommended display area for a user to select.
In an optional embodiment of the present application, the number of the second recommended words corresponding to the first recommended word is greater than 1, and the step 204 of combining the first recommended word and the second recommended word to generate the target recommendation information includes:
and step S21, determining a default second recommended word in at least two second recommended words corresponding to the first recommended word.
And step S22, combining the first recommended word and the default second recommended word to generate target recommended information.
Specifically, when the number of the second recommended words corresponding to the first recommended word is greater than 1, the weight of the second recommended word is determined according to historical screen-up information of the user in a preset period, the use condition of the second recommended word, retrieval information of the user on a search engine, browsing information and the like, and the second recommended word with the largest weight value is used as the default second recommended word. For example, if the user checks the recommended dishes and user evaluation of the hot pot before one day, but does not browse the related information of barbecued meat and crawfish recently, the weight value of the "hot pot" is the largest among the second recommended words "hot pot", "barbecued meat" and "crawfish" corresponding to the first recommended word "good to eat", the "hot pot" is taken as the default second recommended word, and the first recommended word "good to eat" and the default second recommended word "hot pot" are combined to generate the target recommended information "good to eat hot pot".
In an optional embodiment of the present application, in response to the triggering operation on the target recommendation information in step 205, generating the target information according to the first recommendation word and the second recommendation word included in the target recommendation word includes:
and responding to the confirmation operation of the target recommendation information, and generating target information according to the first recommendation words and the default second recommendation words.
If the confirmation operation of the user on the displayed target recommendation information is received, the target recommendation information is determined to meet the actual requirement of the user, and then the target information can be generated according to the first recommendation words and the second recommendation words contained in the target recommendation information. For example, a confirmation operation that the user confirms that the target recommendation information is good to eat the hot pot is received, the target information including the target message of the first recommendation word "good to eat" and the default second recommendation word "hot pot" can be directly generated, the behavior habits of the user can be further analyzed, the target recommendation information is further optimized according to the behavior habits of the user, such as common language words, expression packets and the like, and the target information is generated, such as "good to eat the hot pot". And nearby merchants meeting the requirements of the user can be obtained according to the current position of the user, and the generated target information contains merchant information or merchant positions, such as 'wok of a trade square in good thinking of eating'.
In an optional embodiment of the present application, in response to the triggering operation on the target recommendation information in step 205, generating target information according to a first recommended word and a second recommended word included in the target recommendation information includes:
step S31, responding to a trigger operation on the default second recommended word in the target recommended information, and displaying at least two second recommended words corresponding to the first recommended word in the target recommended information.
And step S32, responding to the selection operation of the at least two second recommended words, and determining the target second recommended word.
And step S33, generating target information according to the first recommended word and the target second recommended word.
In the embodiment of the application, if the user is not satisfied with the default second recommended word provided by the input engine, the user may perform a trigger operation on the default second recommended word, for example, click the default second recommended word, and the input engine displays all the second recommended words corresponding to the first recommended word in the target recommended information in the recommendation display area in response to the trigger operation on the default second recommended word by the user, so that the user can select the second recommended word. And determining a target second recommended word according to the selection operation of the user, and generating target information according to the first recommended word and the target second recommended word.
Referring to fig. 3, a display diagram of a second recommended word provided in an embodiment of the present application is shown. As shown in fig. 2, assuming that the determined default second recommended word is "hot pot" according to the weight value of each second recommended word when the determined first recommended word is "good to eat", target recommendation information is generated according to the first recommended word and the default recommended word, and is displayed in the recommendation display area. If the user is not satisfied with the provided default second recommended word "hot pot", a trigger operation may be performed on the default second recommended word, for example, the default second recommended word "hot pot" is clicked, and the input engine may display, in the recommendation display area, other second recommended words corresponding to the first recommended word "good to eat", for example, "roast meat", "crawfish", and "seafood". The display sequence of the second recommended words is determined according to the weight value corresponding to each second recommended word. Specifically, the weight of the second recommended word may be determined according to historical screen-up information of the user in a preset period, a use condition of the second recommended word, retrieval information of the user on a search engine, browsing information, and the like.
Optionally, in this embodiment of the application, there may also be a plurality of first recommended words determined according to the first scene information, when the number of the first recommended words is greater than 1, a default first recommended word is determined according to a weight value of the first recommended word, and target recommended information is generated and displayed according to the default first recommended word and the second recommended word. The weighted value of the first recommended word can be determined according to the matching degree of the second scene information corresponding to the first recommended word and the first scene information, historical screen information of the user and the like. If the user is not satisfied with the displayed target recommendation information, the input engine responds to the trigger operation of the user by executing the trigger operation on the target recommendation information containing the default first recommendation word, and the target recommendation information generated by combining each first recommendation word and each second recommendation word is displayed in the recommendation display area for the user to select.
Referring to fig. 4, a display diagram of a first recommendation provided in an embodiment of the present application is shown. Assuming that the default first recommended word is determined to be 'together', target recommended information 'going to the dining bar together' containing the default first recommended word 'together' is displayed in the recommended display area, if the user is not satisfied with the displayed target recommended information, more options corresponding to the target recommended information 'going to the dining bar together' can be clicked, and therefore target recommended information generated by combining each first recommended word matched with the first scene information and the second recommended word can be checked.
If the first scene information corresponds to a plurality of first recommended words and at least one first recommended word corresponds to a plurality of second recommended words, determining a first display sequence of the first recommended words according to the weight values of the first recommended words, determining a second display sequence of the second recommended words corresponding to the first recommended words according to the weight values of the second recommended words corresponding to the first recommended words, and determining a display sequence of target recommended information generated by combining the first recommended words and the second recommended words according to the first display sequence and the second display sequence.
Optionally, in this embodiment of the application, if the user is not satisfied with the target recommendation information displayed in the display area, the user may also directly input the message content in the input box, the input engine performs screening on the target recommendation information according to the message content input by the user, and the screened target recommendation information is displayed in the display area, or the target information is directly generated according to the message content input by the user.
And step 206, inputting the target information when the confirmation operation of the target information is received.
In the generation of the target information, whether the generated target information meets the requirements of the user is further judged, and if the confirmation operation of the user on the target information is received, the target information is input. For example, the generated target information is 'good desire to eat chafing dish of a Chinese product square', but the user wants to go to other places, the user can modify the generated target information, for example, the user modifies 'good desire to eat chafing dish of a Wanda square', and only when the user confirms the target information, the target information is input, so that the input target information is prevented from being not in accordance with the expectation of the user.
Optionally, after step 206, the method further includes: and updating the recommended word bank corresponding to the user according to the input target information and the first scene information.
In the application embodiment, the recommendation word bank of the user can be updated according to the matching condition of the input target information and the target recommendation word provided by the input engine and the first scene information corresponding to the target information. Specifically, if the user generates target information according to the target recommendation information, second scene information corresponding to the first recommendation word included in the target recommendation information in the recommendation word library is updated according to the first scene information.
In summary, in the embodiment of the present application, under the condition that a display interface includes an input area, first scene information corresponding to the display interface is obtained, a first recommended word is determined according to the first scene information, and a second recommended word corresponding to the first recommended word is determined; displaying M pieces of target recommendation information based on the first recommendation words and the second recommendation words; target recommendation information can be determined according to the scene information, and accuracy and real-time performance of information recommendation are improved.
When information needs to be input, responding to the trigger operation of the target recommendation information, and generating target information according to a first recommendation word and a second recommendation word contained in the target recommendation information; and under the condition of receiving the confirmation operation of the target information, inputting the target information, thereby improving the efficiency and accuracy of information input.
It should be noted that, in the information recommendation method provided in the embodiment of the present application, 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 an example in which an information recommendation apparatus executes an information recommendation method.
EXAMPLE III
Referring to fig. 5, which shows a structure diagram of an information recommendation apparatus provided in the third embodiment of the present invention, the structure diagram specifically includes:
the first scene information acquiring module 301 is configured to acquire first scene information corresponding to a display interface of an electronic device when the display interface includes an input area.
The first scene information comprises at least one of time, place and affiliated application program corresponding to the display interface.
A recommended word determining module 302, 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.
And a target recommended word output module 303, configured to display M pieces of target recommended information based on the first recommended word and the second recommended word.
The information recommendation device in the embodiment of the present application may be a device, or may also be a component, an integrated circuit, or a chip in a terminal. The device can be mobile electronic equipment or non-mobile electronic equipment. By way of example, the mobile electronic device may be a mobile phone, a tablet Computer, a notebook Computer, a palm top Computer, a vehicle-mounted electronic device, a wearable device, an ultra-mobile Personal Computer (UMPC), a netbook or a Personal Digital Assistant (PDA), or the like, or the electronic device may also be a server, a Network Attached Storage (NAS), a Personal Computer (Personal Computer, PC), a Television (TV), a teller machine, a self-service machine, or the like, and the embodiments of the present application are not particularly limited.
The information recommendation device in the embodiment of the present application may be a device having an operating system. The operating system may be an Android (Android) operating system, an ios operating system, or other possible operating systems, and embodiments of the present application are not limited specifically.
The information recommendation device provided in the embodiment of the present application can implement each process implemented by the device in the method embodiments of fig. 1 to fig. 2, and is not described here again to avoid repetition.
In the embodiment of the application, under the condition that a display interface of electronic equipment comprises an input area, first scene information corresponding to the display interface is obtained, a first recommended word is determined according to the first scene information, and a second recommended word corresponding to the first recommended word is determined; the M pieces of target recommendation information are displayed based on the first recommendation words and the second recommendation words, the target recommendation information can be determined according to scene information, and the real-time performance and the accuracy of information recommendation are improved.
Example four
Referring to fig. 6, which shows a structure diagram of an information recommendation apparatus according to a fourth embodiment of the present invention, the information recommendation apparatus specifically includes:
a recommended word bank generating module 401, configured to generate a recommended word bank corresponding to the user according to the historical screen information of the user and second scene information corresponding to the historical screen information, where the recommended word bank includes a preset first recommended word and a second recommended word, and the preset first recommended word corresponds to the second scene information.
Optionally, the recommendation thesaurus generating module 401 includes:
the high-frequency statement determination submodule 4011 is configured to determine at least two high-frequency statements of the user according to the screen-up frequency of the historical screen-up information of the user;
the clustering submodule 4012 is configured to cluster the at least two high-frequency statements according to the second scene information corresponding to the high-frequency statements, so as to obtain a high-frequency statement group;
the first recommended word determining sub-module 4013 is configured to determine, according to the high-frequency sentence group and a preset similarity condition, first recommended words corresponding to the at least two high-frequency sentences;
the second recommended word determining sub-module 4014 is configured to extract a second recommended word corresponding to the first recommended word in the at least two high-frequency sentences;
and a recommended word bank generating submodule 4015, configured to generate a recommended word bank corresponding to the user according to the first recommended word and the second recommended word.
A first scenario information obtaining module 402, configured to obtain, when a display interface includes an input area, first scenario information corresponding to the display interface, where the first scenario information includes at least one of a time, a place, and an application program corresponding to the display interface.
A recommended word determining module 403, 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.
Optionally, the recommended word determining module 403 includes:
and the recommended word determining sub-module 4031 is configured to search the recommended word library 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.
And a target recommended word output module 404, configured to display M pieces of target recommended information based on the first recommended word and the second recommended word.
Optionally, the number of the second recommended words corresponding to the first recommended word is greater than 1, and the target recommendation information output module 404 includes:
a default second recommended word determining sub-module 4041, configured to determine a default second recommended word in the at least two second recommended words corresponding to the first recommended word;
and the recommended word module generation sub-module 4042 is configured to combine the first recommended word and the default second recommended word to generate target recommendation information.
And a target message generation module 405, configured to respond to a trigger operation on the target recommendation information, and generate target information according to the target recommendation information.
Optionally, the target information generating module 405 includes:
the first target information generating sub-module 4051 is configured to generate, in response to a confirmation operation on the target recommendation information, target information according to the first recommended word and the default second recommended word.
Optionally, the target information generating module 405 includes:
a second recommended word display sub-module 4052, configured to display at least two second recommended words corresponding to a first recommended word in the target recommendation information in response to a trigger operation on the default second recommended word in the target recommendation information;
a target second recommended word determining sub-module 4053, configured to determine a target second recommended word in response to a selection operation on the at least two second recommended words;
the second target message generating sub-module 4054 is configured to generate target information according to the first recommended word and the target second recommended word.
And a target information recommending module 406, configured to perform input with the target information when a confirmation operation on the target information is received.
Optionally, the apparatus further comprises:
and a recommended word bank updating module 407, configured to update the recommended word bank corresponding to the user according to the input target information and the first scene information.
The information recommendation device in the embodiment of the present application may be a device, or may also be a component, an integrated circuit, or a chip in a terminal. The device can be mobile electronic equipment or non-mobile electronic equipment. By way of example, the mobile electronic device may be a mobile phone, a tablet computer, a notebook computer, a palm top computer, a vehicle-mounted electronic device, a wearable device, an ultra-mobile personal computer (UMPC), a netbook or a Personal Digital Assistant (PDA), and the like, and the non-mobile electronic device may be a server, a Network Attached Storage (NAS), a Personal Computer (PC), a Television (TV), a teller machine or a self-service machine, and the like, and the embodiments of the present application are not particularly limited.
The information recommendation device in the embodiment of the present application may be a device having an operating system. The operating system may be an Android (Android) operating system, an ios operating system, or other possible operating systems, and embodiments of the present application are not limited specifically.
The information recommendation device provided in the embodiment of the present application can implement each process implemented by the device in the method embodiments of fig. 1 to fig. 2, and is not described here again to avoid repetition.
In the embodiment of the application, under the condition that a display interface of electronic equipment comprises an input box, first scene information corresponding to the display interface is obtained, a first recommended word is determined according to the first scene information, and a second recommended word corresponding to the first recommended word is determined; displaying M pieces of target recommendation information based on the first recommendation words and the second recommendation words; the target recommendation information can be determined according to the scene information, and the real-time performance and accuracy of the determined target recommendation information are improved.
EXAMPLE five
Optionally, as shown in fig. 7, an electronic device 700 is further provided in this embodiment of the present application, and includes a processor 701, a memory 702, and a program or an instruction stored in the memory 702 and executable on the processor 701, where the program or the instruction is executed by the processor 701 to implement each process of the information recommendation method embodiment, and can achieve the same technical effect, and no further description is provided here to avoid repetition.
It should be noted that the electronic devices in the embodiments of the present application include the mobile electronic devices and the non-mobile electronic devices described above.
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.
Those skilled in the art will appreciate that the electronic device 800 may further comprise a power source (e.g., a battery) for supplying power to the various components, and the power source may be logically connected to the processor 810 via a power management system, so as to manage charging, discharging, and power consumption management functions via the power management system. The electronic device structure shown in fig. 8 does not constitute a limitation of the electronic device, and the electronic device may include more or less components than those shown, or combine some components, or arrange different components, and thus, the description is omitted here.
EXAMPLE six
The embodiment of the present application further provides a readable storage medium, where a program or an instruction is stored on the readable storage medium, and when the program or the instruction is executed by a processor, the program or the instruction implements each process of the above information recommendation method embodiment, and can achieve the same technical effect, and in order to avoid repetition, details are not repeated here.
The processor is the processor in the electronic device described in the above embodiment. The readable storage medium includes a computer readable storage medium, such as a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and so on.
EXAMPLE seven
The 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 each process of the above information recommendation method embodiment, and can achieve the same technical effect, and in order to avoid repetition, the chip is not described here again.
It should be understood that the chips mentioned in the embodiments of the present application may also be referred to as system-on-chip, system-on-chip or system-on-chip, etc.
It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element. Further, it should be noted that the scope of the methods and apparatus of the embodiments of the present application is not limited to performing the functions in the order illustrated or discussed, but may include performing the functions in a substantially simultaneous manner or in a reverse order based on the functions involved, e.g., the methods described may be performed in an order different than that described, and various steps may be added, omitted, or combined. In addition, features described with reference to certain examples may be combined in other examples.
Through the above description of the embodiments, those skilled in the art will clearly understand that the method of the above embodiments can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware, but in many cases, the former is a better implementation manner. Based on such understanding, the technical solutions of the present application may be embodied in the form of a software product, which is stored in a storage medium (such as ROM/RAM, magnetic disk, optical disk) and includes instructions for enabling a terminal (such as a mobile phone, a computer, a server, an air conditioner, or a network device) to execute the method according to the embodiments of the present application.
While the present embodiments have been described with reference to the accompanying drawings, it is to be understood that the invention is not limited to the precise embodiments described above, which are meant to be illustrative and not restrictive, and that various changes may be made therein by those skilled in the art without departing from the spirit and scope of the invention as defined by the appended claims.
Claims (14)
1. An information recommendation method is applied to an electronic device, and the method comprises the following steps:
under the condition that a display interface of the electronic equipment comprises an input area, acquiring first scene information corresponding to the display interface, wherein the first scene information comprises at least one of an application program to which the display interface belongs, time information contained in the display interface and a geographic position of the electronic equipment;
determining a first recommended word according to the first scene information, and determining a second recommended word corresponding to the first recommended word;
and displaying M pieces of target recommendation information based on the first recommendation words and the second recommendation words.
2. The method of claim 1, wherein before determining a first recommended word according to the first scene information and determining a second recommended word corresponding to the first recommended word, the method further comprises:
generating a recommended word bank corresponding to the user according to the historical screen information of the user and second scene information corresponding to the historical screen information, wherein the recommended word bank comprises a preset first recommended word and a preset second recommended word, and the preset first recommended word corresponds to the second scene information;
the determining a first recommended word according to the first scene information and determining a second recommended word corresponding to the first recommended word includes:
and searching a first recommended word corresponding to second scene information matched with the first scene information and a second recommended word corresponding to the first recommended word in the recommended word bank.
3. The method according to claim 2, wherein the generating of the recommended word bank corresponding to the user according to the historical screen information of the user and the second scene information corresponding to the historical screen information includes:
determining at least two high-frequency sentences of the user according to the screen-up frequency of the historical screen-up information of the user;
clustering the at least two high-frequency sentences according to second scene information corresponding to the high-frequency sentences to obtain a high-frequency sentence group;
determining first recommended words corresponding to the at least two high-frequency sentences according to the high-frequency sentence group and a preset similarity condition;
extracting a second word-pushing word corresponding to the first recommended word in the at least two high-frequency sentences;
and generating a recommended word bank corresponding to the user according to the first recommended word and the second recommended word.
4. The method of claim 1, wherein the number of second recommended words corresponding to the first recommended word is greater than 1, and the combining the first recommended word and the second recommended word to generate target recommendation information includes:
determining a default second recommended word in at least two second recommended words corresponding to the first recommended word;
and displaying M pieces of target recommendation information based on the first recommendation words and the default second recommendation words.
5. The method of claim 4, wherein after the displaying the M pieces of target recommendation information based on the first recommendation word and the second recommendation word, further comprising:
and responding to the trigger operation of the target recommendation information, and generating a target message according to the target recommendation information.
6. The method of claim 5, wherein generating a target message according to the target recommendation information in response to the triggering operation on the target recommendation information comprises:
responding to the trigger operation of the default second recommended word in the target recommended information, and displaying at least two second recommended words corresponding to the first recommended word in the target recommended information;
responding to the selection operation of the at least two second recommended words, and determining a target second recommended word;
and generating target information according to the first recommended word and the target second recommended word.
7. An information recommendation device applied to an electronic device, the device comprising:
the electronic equipment comprises a first scene information acquisition module, a second scene information acquisition module and a display interface acquisition module, wherein the first scene information acquisition module is used for acquiring first scene information corresponding to a display interface of the electronic equipment under the condition that the display interface comprises an input area, and the first scene information comprises at least one of an application program of the display interface, time information contained in the display interface and a geographic position of the electronic equipment;
the recommended word determining module is used for determining a first recommended word according to the first scene information and determining a second recommended word corresponding to the first recommended word;
and the target recommendation information output module is used for displaying M pieces of target recommendation information based on the first recommendation words and the second recommendation words.
8. The apparatus of claim 7, further comprising:
a recommended word bank generating module, configured to generate a recommended word bank corresponding to the user according to historical screen information of the user and second scene information corresponding to the historical screen information, where the recommended word bank includes a preset first recommended word and a second recommended word, and the preset first recommended word corresponds to the second scene information;
the recommended word determining module comprises:
and the recommended word determining sub-module is used for searching a first recommended word corresponding to second scene information matched with the first scene information and a second recommended word corresponding to the first recommended word in the recommended word bank.
9. The apparatus of claim 8, wherein the recommended word bank generating module comprises:
the high-frequency statement determining submodule is used for determining at least two high-frequency statements of the user according to the screen-up frequency of the historical screen-up information of the user;
the clustering submodule is used for clustering the at least two high-frequency sentences according to second scene information corresponding to the high-frequency sentences to obtain a high-frequency sentence group;
the first recommended word determining sub-module is used for determining first recommended words corresponding to the at least two high-frequency sentences according to the high-frequency sentence group and a preset similarity condition;
the second recommended word determining submodule is used for extracting a second recommended word corresponding to the first recommended word in the at least two high-frequency sentences;
and the recommended word bank generating submodule is used for generating a recommended word bank corresponding to the user according to the first recommended word and the second recommended word.
10. The apparatus of claim 7, wherein the number of the second recommended words corresponding to the first recommended word is greater than 1, and the target recommendation information output module includes:
the default second recommended word determining sub-module is used for determining a default second recommended word in at least two second recommended words corresponding to the first recommended word;
and the recommended word module generation submodule is used for displaying M pieces of target recommended information based on the first recommended word and the default second recommended word.
11. The apparatus of claim 10, further comprising:
and the target message generation module is used for responding to the confirmation operation of the target recommendation information and generating a target message according to the target recommendation information.
12. The apparatus of claim 10, wherein the target message generation module comprises:
the second recommended word display sub-module is used for responding to the triggering operation of the default second recommended word in the target recommended information and displaying at least two second recommended words corresponding to the first recommended word in the target recommended information;
the target second recommended word determining submodule is used for responding to the selection operation of the at least two second recommended words and determining a target second recommended word;
and the second target message generation submodule is used for generating target information according to the first recommended word and the target second recommended word.
13. An electronic device comprising a processor, a memory, and a program or instructions stored on the memory and executable on the processor, the program or instructions when executed by the processor implementing the steps of the information recommendation method of any of claims 1 to 6.
14. A readable storage medium, on which a program or instructions are stored, which when executed by a processor, implement the steps of the information recommendation method according to any one of claims 1 to 6.
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| PCT/CN2021/139657 WO2022135339A1 (en) | 2020-12-25 | 2021-12-20 | Message content input method and apparatus, and electronic device |
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| WO2022135339A1 (en) * | 2020-12-25 | 2022-06-30 | 维沃移动通信有限公司 | Message content input method and apparatus, and electronic device |
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| CN117540057B (en) * | 2024-01-10 | 2024-04-30 | 广东省电信规划设计院有限公司 | AIGC-based retrieval guiding method and AIGC-based retrieval guiding device |
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