Information recommendation method, device and electronic equipment

Abstract

The present application discloses an information recommendation method, device and electronic device, which belongs to the field of communication technology and can solve the problem that the text input process is cumbersome and time-consuming. The above method includes: receiving a first input from a user on a first interface; in response to the above first input, matching candidate words from a vocabulary based on the character string corresponding to the above first input and the above first interface, and displaying the above candidate words; wherein the above vocabulary stores keywords and the mapping relationship between the keywords and the first interface. The present application is applied to the scenario of text input.

Description

Technical Field

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

[0002] With the development of electronic technology, there are more and more scenarios where users input text on electronic devices. Currently, when a user inputs a character string, the electronic device can recommend candidate words corresponding to the character string, and the user selects a target candidate word from the candidate words.

[0003] In the related art, when an electronic device recommends candidate words to a user, it can read the candidate words corresponding to the input string from the word library for recommendation. However, since a large number of words are usually stored in the word library, each time the electronic device recommends a candidate word to a user, it needs to traverse a large number of words stored in the entire word library to determine the candidate words corresponding to the input string, resulting in low efficiency in recommending candidate words to the user. In addition, for the same string input by the user, there may be multiple matching items in the word library, and the electronic device will recommend the above multiple matching items as candidate words. As a result, the accuracy of recommending candidate words to the user is low, thereby affecting the user's input efficiency. Summary of the invention

[0004] The purpose of the embodiments of the present application is to provide an information recommendation method that can solve the problem that the text input process is complicated and time-consuming.

[0005] In order to solve the above technical problems, this application is implemented as follows:

[0006] In a first aspect, an embodiment of the present application provides an information recommendation method, the method comprising: receiving a first input from a user on a first interface; in response to the first input, matching candidate words from a vocabulary based on a character string corresponding to the first input and the first interface, and displaying the candidate words; wherein the vocabulary stores keywords and a mapping relationship between the keywords and the first interface.

[0007] In a second aspect, an embodiment of the present application provides an information recommendation device, which includes: the above-mentioned device includes: a receiving module, a processing module and a display module, wherein: the above-mentioned receiving module is used to receive a first input from a user on a first interface; the above-mentioned processing module is used to respond to the above-mentioned first input received by the above-mentioned receiving module, and match candidate words from a vocabulary based on the character string corresponding to the above-mentioned first input and the above-mentioned first interface; the above-mentioned display module is used to display the above-mentioned candidate words matched by the above-mentioned processing module from the vocabulary; wherein the above-mentioned vocabulary stores keywords and the mapping relationship between the above-mentioned keywords and the above-mentioned first interface.

[0008] In a third aspect, an embodiment of the present application provides an electronic device, which includes a processor, a memory, and a program or instruction stored in the memory and executable on the processor, wherein the program or instruction, when executed by the processor, implements the steps of the method described in the first aspect.

[0009] In a fourth aspect, an embodiment of the present application provides a readable storage medium, on which a program or instruction is stored, and when the program or instruction is executed by a processor, the steps of the method described in the first aspect are implemented.

[0010] In a fifth aspect, an embodiment of the present application provides a chip, comprising a processor and a communication interface, wherein the communication interface is coupled to the processor, and the processor is used to run a program or instruction to implement the method described in the first aspect.

[0011] In a sixth aspect, an embodiment of the present application provides a computer program product, which is stored in a non-volatile storage medium and is executed by at least one processor to implement the method described in the first aspect.

[0012] In the embodiment of the present application, the electronic device stores keywords and the mapping relationship between the keywords and the first interface in the word library, so that when the user inputs a character string in the first interface, the electronic device can determine the candidate words matching the character string and the first interface from the word library based on the character string and the first interface. In this way, the electronic device can recommend candidate words matching the current input interface to the user, thereby recommending candidate words that better meet the user's input requirements on the current input interface, thereby improving the flexibility and accuracy of recommending candidate words to the user. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] Figure 1 is a flow chart of the information recommendation method provided by an embodiment of the present application;

[0014] Figure 2 This is one of the structural schematic diagrams of an information recommendation device provided in an embodiment of the present application;

[0015] Figure 3 This is one of the hardware structure diagrams of an electronic device provided in an embodiment of the present application;

[0016] Figure 4 This is the second schematic diagram of the hardware structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0017] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0018] The terms "first", "second", etc. in the specification and claims of the present application are used to distinguish similar objects, and are not used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable under appropriate circumstances, so that the embodiments of the present application can be implemented in an order other than those illustrated or described here, and the objects distinguished by "first", "second", etc. are generally of one type, and the number of objects is not limited. For example, the first object can be one or more. In addition, "and / or" in the specification and claims represents at least one of the connected objects, and the character " / " generally indicates that the objects associated with each other are in an "or" relationship.

[0019] The information recommendation method provided by the embodiment of the present application is described in detail below through specific embodiments and their application scenarios in conjunction with the accompanying drawings.

[0020] The information recommendation method provided in the embodiment of the present application can be applied to the scenario of text input.

[0021] The embodiments of the present application provide an information recommendation method, device and electronic device. Since users usually use various symbols to indicate pauses in text content and the tone to be expressed in the text content (such as complete sentences or words) with complete semantics that they input. Therefore, when the information recommendation device detects that the content displayed on the screen by the user this time includes the first symbol, the text input by the user can be split based on the target characters and the first symbol in the text input by the user, so that the target text containing the complete words that the user wants to input can be extracted from the text input by the user, and the complete words contained in the target text can be stored in the word library. So that when the user inputs the keyword again, the keyword can be recommended to the user as a candidate word.

[0022] Figure 1 A flow chart of a display method provided in an embodiment of the present application is shown.

[0023] like Figure 1 As shown, the information recommendation method provided in the embodiment of the present application may include the following steps 101 and 102:

[0024] Step 101: Receive a first input from a user on a first interface.

[0025] In the embodiment of the present application, the above-mentioned first interface may include any one of the following: a conversation window interface, a text input interface.

[0026] Optionally, in an embodiment of the present application, the first interface includes an information input area and an information display area. Exemplarily, the information input area is used to input a character string, for example, the information input area may be an input method interface. Exemplarily, the information display area is used to display text information entered by the user on the screen.

[0027] Exemplarily, the first input may be a character string input by a user in the information input area.

[0028] Step 102: In response to the first input, based on the character string corresponding to the first input and the first interface, match candidate words from a vocabulary, and display the candidate words.

[0029] The above-mentioned word library stores keywords and mapping relationships between keywords and the first interface. It is understandable that the above-mentioned word library may store multiple mapping relationships, one mapping relationship is a mapping relationship between at least one keyword and an interface, and / or one mapping relationship may be a mapping relationship between at least one keyword and an interface type.

[0030] In an embodiment of the present application, the information recommendation device may display candidate words in a candidate word display area.

[0031] Exemplarily, the candidate word display area may be an area on an input method interface, or the candidate word display area may be a floating window.

[0032] In the embodiment of the present application, when the user inputs a character string on the first interface, the information recommendation device can search for keywords that have a mapping relationship with the first interface (i.e., keywords associated with the first interface) from the word library, and use the above keywords as candidate keywords. Then, based on the character string input by the user, the information recommendation device can search for keywords that match the character string input by the user from the above keywords that have a mapping relationship with the first interface (i.e., the above candidate keywords) as candidate words.

[0033] For example, taking the first interface as conversation interface 1, if the vocabulary stores keyword A, keyword B, keyword C and keyword D that have a mapping relationship with the first interface, when the user enters character string 1 in conversation interface 1, the keyword that matches character string 1 can be determined from the above four keywords that have a mapping relationship with conversation interface 1, and the keyword can be recommended to the user as a candidate word.

[0034] Optionally, in the embodiments of the present application, the process by which the information recommendation device determines the keywords that match the string input by the user from the keywords associated with the first interface includes at least the following three methods:

[0035] Method 1: Memory-based prioritized word output. That is, if the word library includes a string that is the same as the first string typed by the user on the first interface (i.e., the string currently typed by the user through the physical keyboard or virtual keyboard), the information recommendation device may display the text corresponding to the string (i.e., the keyword associated with the keyword library and the string corresponding to the keyword) at a position closer to the front of the candidate word display area.

[0036] For example, if the string typed by the user on the first interface is "hanyufei", and the word library stores "韩语菲" and "hanyufei" in an associated manner, the information recommendation device obtains the text "韩语菲" in the word library and displays "韩语菲" at a position closer to the front of the candidate word display area, that is, recommends "韩语菲" as the first candidate word to the user.

[0037] Method 2: Prefix combination with memory-based word output. That is, when the user types a string on the first interface, if the information recommendation device detects that there is a string in the word library that includes the first string currently typed by the user, the information recommendation device may display the text corresponding to the string at a position closer to the front of the candidate word display area.

[0038] For example, if the string typed by the user on the first interface is "hanyu", and the word library stores "韩语菲" and "hanyufei" in an associated manner, the information recommendation device obtains the text "韩语菲" in the word library and displays "韩语菲" at a position closer to the front of the candidate word display area, that is, recommends "韩语菲" as the first candidate word to the user.

[0039] Method 3: Word prefix association combined with memory-based word output. That is, when the user types a string on the first interface and selects the candidate word corresponding to the string to be input onto the screen, and after the candidate word is input onto the text input interface, if there is a character in the word library that includes the first character input by the user onto the text input interface this time, the information recommendation device obtains the character in the word library and displays the characters other than the first character in the character at a position closer to the front of the candidate word display area.

[0040] For example, when the user types "han" and selects "韩" to be input onto the screen, when the information recommendation device detects that there is "韩语菲" including the character "韩" in the word library, the information recommendation device may obtain the text "韩语菲" in the word library and display "语菲" at a position closer to the front of the candidate word display area.

[0041] In the information recommendation method provided by the present application, the electronic device stores keywords and the mapping relationship between the keywords and the first interface in a thesaurus, so that when the user enters a string on the first interface, the candidate words matching the string and the first interface can be determined from the thesaurus based on the string and the first interface. In this way, the electronic device can recommend candidate words that match the current input interface for the user, so as to recommend candidate words that more meet the input requirements of the user on the current input interface, improving the flexibility and accuracy of recommending candidate words for the user.

[0042] Optionally, in the embodiments of the present application, the information recommendation device may extract keywords from the target text displayed on the first interface, and save the above keywords and the mapping relationship between the above keywords and the first interface in the thesaurus.

[0043] Exemplarily, before step 101, the information recommendation method provided by the embodiments of the present application further includes the following steps A1 to A3:

[0044] Step A1: When it is detected that the content input on the first interface includes a first symbol, obtain the target text.

[0045] Step A2: Extract the keywords in the above target text.

[0046] Step A3: Store the above keywords and the above mapping relationship in the thesaurus correspondingly.

[0047] Optionally, in the embodiments of the present application, the content input on the first interface is the text entered by the user on the screen.

[0048] Optionally, in the embodiments of the present application, the above target text includes: the characters between the target character entered by the user and the first symbol; the above target character is: the first character entered by the user, or, the second symbol displayed in the first interface before the first symbol.

[0049] In one example, when the target character is the first character entered by the user, the target text is the text between the first character entered by the user and the first symbol currently entered. For example, if the text content entered by the user is "Tomorrow is Lanyu Fei's birthday.", then the target text is the text between the character "明" and ".".

[0050] In another example, when the target character is the second symbol entered on the screen before the first symbol entered by the user this time, the target text is the text between the second symbol and the first symbol. For example, if the text content entered by the user is "Tomorrow the weather is very good. We are going to help Lanyu Fei move.", then the target text is the text between "," and ".".

[0051] It should be noted that, when the information recommendation device detects both the first character input by the user and the second character from the input text, the information recommendation device will determine the second symbol as the target character.

[0052] Optionally, in an embodiment of the present application, during the process of the user inputting text, the information recommendation device may perform real-time or periodic detection (e.g., once every 5 seconds) on the content input by the user (i.e., the content currently displayed on the screen) to determine whether it contains the first symbol.

[0053] Optionally, in the embodiment of the present application, when the information recommendation device detects that the content displayed on the screen by the user includes the first symbol, the first text can be determined from the text input by the user, and then the target character is detected in the first text, and the target character is a character in the first text that meets the predetermined condition. The first text includes: all the text input by the user, the text input by the user within a predetermined time before inputting the first symbol, and the text composed of a predetermined number of characters input by the user before inputting the first symbol (for example, 30 characters input by the user before inputting the first symbol).

[0054] Optionally, in the embodiment of the present application, the information recommendation device can detect in real time whether the text input by the user contains the first character. Therefore, when the user currently inputs (on the screen) a symbol, the information recommendation device will obtain the target text once to ensure that all the content input by the user can be detected.

[0055] Optionally, in the embodiment of the present application, the first symbol and the second symbol are both target symbols, wherein the target symbol includes any one of the following: punctuation marks, separators, wherein separators include: line breaks, space characters.

[0056] Usually, users will use various symbols to indicate pauses in text content and the tone to be expressed in input text with complete semantics (such as complete sentences or words). In this way, in a text, the text content between the two punctuation marks before and after is usually a sentence or a text containing complete words (such as names of people or places). Different symbols express different meanings.

[0057] Example 1: Regarding punctuation marks, some punctuation marks (such as ",",",",".") are usually used to express pauses in text content, and some punctuation marks (such as "!" "?") are usually used to express the tone that the user wants to express corresponding to the text content.

[0058] Example 2: Regarding separators, separators are usually used to separate and split text content. For example, when it is detected that the user is currently inputting a space character, it means that the user has entered a complete sentence or a word. At this time, the information recommendation device can obtain the target text in the text entered by the user based on the space character and the symbol before the space character, thereby ensuring the integrity of the obtained target text.

[0059] For example, suppose the text entered by the user is "Tomorrow the weather will be very good. Let's meet at Pujun East Road at 10 o'clock and go to Guigongfang for morning tea together." Since there are "," and "." in the text, it means that there is a complete sentence between "," and ".". Therefore, the information recommendation device uses the text between "," and "." as the target text to obtain a sentence.

[0060] Optionally, in an embodiment of the present application, when obtaining a target text in the text input by the user, the information recommendation device may perform word segmentation or semantic recognition on the target text, extract keywords in the target text, and obtain at least one keyword in the target text.

[0061] Exemplarily, the above keywords may be words or phrases containing specific semantics in the target text, and the above keywords include at least one of the following: names of persons, places, institutions, and proper nouns.

[0062] It should be noted that the information recommendation device can extract one or more keywords from the target text, which is not limited in the embodiment of the present application.

[0063] In this way, the information recommendation device can extract keywords with complete semantics based on the target text input by the user on the first interface. Since the keywords are extracted from the first interface, they are more consistent with the input intention of the user on the first interface.

[0064] Optionally, in the embodiment of the present application, when keywords are extracted from the target text of the first interface, the information recommendation device may establish a mapping relationship between the first interface and the keywords.

[0065] Exemplarily, the information recommendation device may automatically establish the mapping relationship between the first interface and the keywords, or the mapping relationship between the first interface and the keywords may be established by a user triggering the establishment of the mapping relationship.

[0066] For example, taking the first interface as a conversation interface, if the keywords include keyword A, keyword B, keyword C and keyword B, the information recommendation device can store the above 4 keywords in the vocabulary, and generate a mapping relationship between each of the above 4 keywords and the conversation interface, obtain 4 mapping relationships, and store the above 4 mapping relationships in the vocabulary respectively.

[0067] In this way, the information recommendation device can save the keywords extracted from the target text on the first interface and the mapping relationship of the first interface in the thesaurus. When the user enters a string on the first interface, the information recommendation device can recommend candidate words that conform to the user's input habits on the first interface according to the mapping relationship between the first interface and the keywords.

[0068] Further optionally, in the embodiment of the present application, storing the keyword in the thesaurus in step A3 above includes the following step B1:

[0069] Step B1: Associatively store the keyword and the string corresponding to the keyword in the thesaurus.

[0070] Exemplarily, after the information recommendation device extracts the keyword from the target text, it can obtain the string corresponding to the keyword (such as pinyin), and then store the corresponding relationship between the string and the string corresponding to the keyword in the thesaurus. In this way, the information recommendation device can find the keyword corresponding to the string based on this corresponding relationship in the thesaurus, and thus display the keyword to the user as a candidate word, improving the recommendation efficiency of the candidate word.

[0071] Exemplarily, the string corresponding to the above keyword may include at least one of the following: the pinyin of the keyword, the pinyin with a relatively high similarity to the pinyin of the keyword (for example, if the pinyin of the keyword is "lanyufei", the pinyin close to the pinyin of the keyword may be "hanyufei" or lanyuwei, etc.), the foreign language translation of the keyword (for example, if the keyword is "蓝语菲", the English translation of the keyword, such as "Lanyufei", can be obtained and saved).

[0072] Further optionally, in the embodiment of the present application, step A2 above includes the following steps C1 to C3:

[0073] Step C1: Segment the target text to obtain N candidate segments.

[0074] Step C2: Receive a second input from the user for the target candidate segment among the N candidate segments.

[0075] Step C3: In response to the second input, use the target candidate segment as the keyword.

[0076] Exemplarily, the above first input includes: any feasible input, such as touch input, gesture input, voice input.

[0077] Exemplarily, the information recommendation device may perform a segmentation operation on the target text using a segmentation method such as character matching, understanding method or statistical method to obtain N candidate segmentations, and determine the target candidate segmentation as a keyword based on the user's input operation on the target candidate segmentation among the N candidate segmentations.

[0078] Furthermore, the information recommendation device may display the N candidate participles in the keyword display area, and the user may select (eg, check) the desired candidate participle in the keyword selection area. Then, the information recommendation device may determine the candidate participle selected by the user as a keyword.

[0079] For example, assuming that the target text is "Han Yufei eats hot pot at Restaurant A", the information recommendation device can perform syntactic analysis on the target text to obtain candidate participles such as "Han Yufei", "Restaurant A", and "hot pot", and display these candidate participles in the keyword display area. The user can click or check the candidate participle "Han Yufei" to determine the candidate participle as a keyword. In this way, the information recommendation device can determine the keyword based on the user's selection operation on the candidate participle, thereby obtaining the keyword required by the user.

[0080] Exemplarily, the text storage device can use a word segmentation method such as character matching, understanding method or statistical method to perform word segmentation operation on the target text, obtain word units in the target text, and then establish a machine learning model based on a machine learning algorithm, using the word features and sentence features of the word units in the target text to extract keywords in the target text. Furthermore, the text storage device can obtain the word features of the word unit and the sentence features of the word unit in the corresponding target text, and the word features of the word unit refer to the word unit's part of speech features and named entity features, etc.

[0081] It should be noted that the part-of-speech feature of the above-mentioned word unit refers to the part of speech of the word unit, such as noun or verb. It is understandable that, under normal circumstances, word units with certain part-of-speech features are more likely to become keywords, for example, word units with noun features. The named entity feature of the above-mentioned word unit refers to whether the word unit is a named entity. Under normal circumstances, word units that are generally named entities are more likely to become keywords.

[0082] Furthermore, the sentence features of the above-mentioned word units in the corresponding target text refer to the features of the word units in the target text, for example, the part-of-speech features of the preceding compound words of the word unit in the target text, the part-of-speech features of the following compound words, the sentence position features, and the dependency features.

[0083] For example, assuming that the target text is "Han Yufei eats hot pot in Restaurant A", the information recommendation device can perform syntactic understanding analysis on the target text to obtain word units such as "Han Yufei", "in", "Restaurant A", "eat", and "hot pot", and obtain the word features of these word units (such as "Han Yufei" is a person's name, "Restaurant A" is a place name, and "eat" is a verb) and sentence features (such as "hot pot" is a noun object, "Han Yufei" is a subject, and "Han Yufei" and "eat" are in a subject-predicate relationship) based on the established machine learning model, and then use the word features of the word units and the sentence features to extract the keywords in the target text, that is, "Han Yufei" and "Restaurant A". In this way, the text storage device can automatically and intelligently extract the keywords in the target text, thereby improving the efficiency of keyword extraction.

[0084] Further optionally, in the embodiment of the present application, after the above step A2, the display method provided in the embodiment of the present application further includes the following steps D1 and D2:

[0085] Step D1: Display keywords.

[0086] Step D2: receiving a third input of a keyword from the user.

[0087] In combination with the above step D2, the above step A3 of storing the above keywords into the vocabulary includes the following step D3:

[0088] Step D3: In response to the second input, the keyword is stored in the vocabulary.

[0089] Exemplarily, after extracting at least one keyword from the target text, the information recommendation device may display the at least one keyword in a predetermined display manner. The predetermined display manner includes at least one of the following: displaying the at least one keyword above the target text, highlighting or highlighting the at least one keyword in the target text, and displaying the at least one keyword in the keyword display interface.

[0090] Exemplarily, after the information recommendation device displays the at least one keyword, the user can select or click any of the at least one keyword (i.e., the third input) to store any of the at least one keyword in the word library. In this way, the user can store keywords in a targeted manner according to needs, which improves the flexibility of storing keywords, further ensures that the keywords stored in the word library can be effectively used, and saves storage space of the word library.

[0091] In the information recommendation method provided in the embodiment of the present application, since users usually use various symbols to indicate pauses in the text content and the tone to be expressed in the text content (such as complete sentences or words) with complete semantics that they input. Therefore, when the information recommendation device detects that the content displayed on the screen by the user this time includes the first symbol, it can perform text segmentation on the text that the user has input based on the target characters and the first symbol in the text that the user has input, so that the target text containing the complete words that the user wants to input can be extracted from the text that the user has input, and the complete words contained in the target text are stored in the word library. So that when the user inputs the keyword again, the keyword can be recommended to the user as a candidate word.

[0092] It should be noted that the information recommendation method provided in the embodiment of the present application can be executed by an information recommendation device or a control module in the information recommendation device for executing the information recommendation method. In the embodiment of the present application, the information recommendation device provided in the embodiment of the present application is described by taking the information recommendation device executing the information recommendation method as an example.

[0093] The present application embodiment provides an information recommendation device, such as Figure 2 As shown, the information recommendation device includes: a receiving module 401, a processing module 402 and a display module 403, wherein: the above-mentioned receiving module 401 is used to receive a first input from a user on a first interface; the above-mentioned processing module 402 is used to match candidate words from a vocabulary based on the character string corresponding to the above-mentioned first input and the above-mentioned first interface in response to the above-mentioned first input received by the above-mentioned receiving module 401; the above-mentioned display module 403 is used to display the above-mentioned candidate words matched by the above-mentioned processing module 402 from the vocabulary; wherein the above-mentioned vocabulary stores keywords and the mapping relationship between the above-mentioned keywords and the above-mentioned first interface.

[0094] In the information recommendation device provided in the embodiment of the present application, the electronic device stores keywords and the mapping relationship between the keywords and the first interface in the word library, so that when the user inputs a character string in the first interface, the electronic device can determine the candidate words matching the character string and the first interface from the word library based on the character string and the first interface. In this way, the electronic device can recommend candidate words matching the current input interface to the user, thereby recommending candidate words that better meet the user's input requirements on the current input interface, thereby improving the flexibility and accuracy of recommending candidate words to the user.

[0095] Optionally, in an embodiment of the present application, the above-mentioned device also includes: an acquisition module 404 and a storage module 405, wherein: the above-mentioned acquisition module 404 is used to acquire the target text when it is detected that the content input on the above-mentioned first interface includes the first symbol; the above-mentioned target text includes: the characters between the target character input by the user and the above-mentioned first symbol; the above-mentioned target character is: the first character input by the user, or, the second symbol displayed in the above-mentioned first interface before the above-mentioned first symbol; the above-mentioned processing module 402 is also used to extract keywords from the above-mentioned target text acquired by the above-mentioned acquisition module 404; the above-mentioned storage module 405 is used to store the above-mentioned keywords extracted by the above-mentioned processing module 402 and the above-mentioned mapping relationship in the above-mentioned vocabulary.

[0096] Optionally, in the embodiment of the present application, the first symbol and the second symbol are both target symbols, wherein the target symbol includes any one of the following: punctuation marks, separators, wherein the separators include: line breaks, space characters.

[0097] Optionally, in the embodiment of the present application, the storage module 405 is specifically used to associate the keywords with the character strings corresponding to the keywords and store them in a vocabulary.

[0098] Optionally, in an embodiment of the present application, the processing module 402 is specifically used to segment the target text to obtain N candidate segmentations; the receiving module 401 is also used to receive a second input from a user regarding a target candidate segmentation among the N candidate segmentations obtained by the processing module 402; the processing module 402 is specifically used to respond to the second input received by the receiving module 401 and use the target candidate segmentation as a keyword.

[0099] Optionally, in an embodiment of the present application, the above-mentioned display module 403 is also used to display the above-mentioned keywords; the above-mentioned receiving module 401 is also used to receive a third input from a user for the keywords displayed by the above-mentioned display module 403; the above-mentioned storage module 405 is specifically used to store the above-mentioned keywords into the vocabulary in response to the above-mentioned third input received by the above-mentioned receiving module 401.

[0100] The information recommendation device in the embodiment of the present application can be a device, or a component, integrated circuit, or chip in a terminal. The device can be a mobile electronic device or a non-mobile electronic device. For example, the mobile electronic device can be a mobile phone, a tablet computer, a laptop computer, a PDA, an in-vehicle electronic device, a wearable device, an ultra-mobile personal computer (UMPC), a netbook, or a personal digital assistant (PDA), etc. The non-mobile electronic device can be a server, a network attached storage (NAS), a personal computer (PC), a television (TV), a teller machine or a self-service machine, etc., which is not specifically limited in the embodiment of the present application.

[0101] 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 operating system, an iOS operating system, or other possible operating systems, which are not specifically limited in the embodiment of the present application.

[0102] The information recommendation device provided in the embodiment of the present application can achieve Figure 1 To avoid repetition, the various processes implemented by the method embodiment are not described here.

[0103] Optional, such as Figure 3 As shown, an embodiment of the present application also provides an electronic device 500, including a processor 501, a memory 502, and a program or instruction stored in the memory 502 and executable on the processor 501. When the program or instruction is executed by the processor 501, each process of the above-mentioned information recommendation method embodiment is implemented, and the same technical effect can be achieved. To avoid repetition, it will not be described here.

[0104] It should be noted that the electronic devices in the embodiments of the present application include the mobile electronic devices and non-mobile electronic devices mentioned above.

[0105] Figure 4 A schematic diagram of the hardware structure of an electronic device to implement an embodiment of the present application.

[0106] The electronic device 100 includes but is not limited to components such as a radio frequency unit 101, a network module 102, an audio output unit 103, an input unit 104, a sensor 105, a display unit 106, a user input unit 107, an interface unit 108, a memory 109, and a processor 110.

[0107] Those skilled in the art will appreciate that the electronic device 100 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 110 through a power management system, thereby implementing functions such as managing charging, discharging, and power consumption management through the power management system. Figure 4 The electronic device structure shown in the figure does not constitute a limitation on the electronic device. The electronic device may include more or fewer components than shown in the figure, or combine certain components, or arrange the components differently, which will not be described in detail here.

[0108] Among them, the above-mentioned user input unit 107 is used to receive the first input of the user on the first interface; the above-mentioned processor 110 is used to match candidate words from the vocabulary in response to the above-mentioned first input received by the above-mentioned user input unit 107, based on the character string corresponding to the above-mentioned first input and the above-mentioned first interface; the above-mentioned display unit 106 is used to display the above-mentioned candidate words matched by the above-mentioned processor 110 from the vocabulary; wherein the above-mentioned vocabulary stores keywords and the mapping relationship between the above-mentioned keywords and the above-mentioned first interface.

[0109] In the electronic device provided in the embodiment of the present application, the electronic device stores keywords and the mapping relationship between the keywords and the first interface in the word library, so that when the user inputs a string in the first interface, the candidate words matching the string and the first interface can be determined from the word library based on the string and the first interface. In this way, the electronic device can recommend candidate words matching the current input interface to the user, thereby recommending candidate words that better meet the user's input requirements on the current input interface, thereby improving the flexibility and accuracy of recommending candidate words to the user.

[0110] Optionally, in an embodiment of the present application, the processor 110 is used to obtain a target text when it is detected that the content input on the first interface includes a first symbol; the target text includes: characters between the target character input by the user and the first symbol; the target character is: the first character input by the user, or, the second symbol displayed on the first interface before the first symbol; the processor 110 is also used to extract keywords from the target text; the memory 109 is used to store the keywords extracted by the processor 110 and the mapping relationship in the vocabulary.

[0111] Optionally, in the embodiment of the present application, the first symbol and the second symbol are both target symbols, wherein the target symbol includes any one of the following: punctuation marks, separators, wherein the separators include: line breaks, space characters.

[0112] Optionally, in an embodiment of the present application, the memory 109 is specifically used to associate the keywords with the character strings corresponding to the keywords and store them in a vocabulary.

[0113] Optionally, in an embodiment of the present application, the processor 110 is specifically used to segment the target text to obtain N candidate segmentations; the user input unit 107 is also used to receive a second input from a user for a target candidate segmentation among the N candidate segmentations obtained by the processor 110; the processor 110 is specifically used to respond to the second input received by the user input unit 107 and use the target candidate segmentation as a keyword.

[0114] Optionally, in an embodiment of the present application, the display unit 106 is also used to display the keywords; the user input unit 107 is also used to receive a third input from a user for the keywords displayed on the display unit 106; the memory 109 is specifically used to store the keywords in the vocabulary in response to the third input received by the user input unit 107.

[0115] The beneficial effects of various implementations in this embodiment can be specifically referred to the beneficial effects of the corresponding implementations in the above method embodiment. To avoid repetition, they will not be described again here.

[0116] It should be understood that in the embodiment of the present application, the input unit 104 may include a graphics processor (Graphics Processing Unit, GPU) 1041 and a microphone 1042, and the graphics processor 1041 processes the image data of the static picture or video obtained by the image capture device (such as a camera) in the video capture mode or the image capture mode. The display unit 106 may include a display panel 1061, and the display panel 1061 may be configured in the form of a liquid crystal display, an organic light emitting diode, etc. The user input unit 107 includes a touch panel 1071 and other input devices 1072. The touch panel 1071 is also called a touch screen. The touch panel 1071 may include two parts: a touch detection device and a touch controller. Other input devices 1072 may include but are not limited to a physical keyboard, a function key (such as a volume control button, a switch button, etc.), a trackball, a mouse, and a joystick, which will not be repeated here. The memory 109 can be used to store software programs and various data, including but not limited to applications and operating systems. The processor 110 can integrate an application processor and a modem processor, wherein the application processor mainly processes the operating system, the user interface, and the application program, etc., and the modem processor mainly processes wireless communication. It is understandable that the above-mentioned modem processor may not be integrated into the processor 110.

[0117] An embodiment of the present application also provides a readable storage medium, on which a program or instruction is stored. When the program or instruction is executed by a processor, the various processes of the above-mentioned storage method embodiment are implemented and the same technical effect can be achieved. To avoid repetition, it will not be repeated here.

[0118] The processor is a processor in the electronic device described in the above embodiment. The readable storage medium includes a computer readable storage medium, such as a computer read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0119] An embodiment of the present application further provides a chip, which includes a processor and a communication interface, wherein the communication interface is coupled to the processor, and the processor is used to run programs or instructions to implement the various processes of the above-mentioned information recommendation method embodiment, and can achieve the same technical effect. To avoid repetition, it will not be repeated here.

[0120] An embodiment of the present application provides a computer program product, which is stored in a non-volatile storage medium and is executed by at least one processor to implement the method as described in the first aspect.

[0121] It should be understood that the chip mentioned in the embodiments of the present application can also be called a system-level chip, a system chip, a chip system or a system-on-chip chip, etc.

[0122] It should be noted that, in this article, the terms "comprise", "include" or any other variant thereof are intended to cover non-exclusive inclusion, so that the process, method, article or device including a series of elements includes not only those elements, but also includes other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "comprise one..." do not exclude the presence of other identical elements in the process, method, article or device including the element. In addition, it should be pointed out that the scope of the methods and devices in the embodiments of the present application is not limited to performing functions in the order shown or discussed, and may also include performing functions in a substantially simultaneous manner or in reverse order according to the functions involved, for example, the described method may be performed in an order different from that described, and various steps may also be added, omitted, or combined. In addition, the features described with reference to certain examples may be combined in other examples.

[0123] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus a necessary general hardware platform, and of course by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present application, or the part that contributes to the prior art, can be embodied in the form of a software product, which is stored in a storage medium (such as ROM / RAM, a magnetic disk, or an optical disk), and includes a number of instructions for a terminal (which can be a mobile phone, a computer, a server, an air conditioner, or a network device, etc.) to execute the methods described in each embodiment of the present application.

[0124] The embodiments of the present application are described above in conjunction with the accompanying drawings, but the present application is not limited to the above-mentioned specific implementation methods. The above-mentioned specific implementation methods are merely illustrative and not restrictive. Under the guidance of the present application, ordinary technicians in this field can also make many forms without departing from the purpose of the present application and the scope of protection of the claims, all of which are within the protection of the present application.

Claims

1. An information recommendation method, characterized in that: The method comprises: In the case where it is detected that the content inputted in the first interface includes a first symbol, a target text is obtained; the target text includes: characters between a target character inputted by a user and the first symbol, the target character is: the first character inputted by the user or a second symbol displayed in the first interface before the first symbol; the first symbol and the second symbol are both target symbols; the target symbol includes any one of the following: punctuation marks, separators; Extracting keywords from the target text; storing the keyword and the mapping relationship between the keyword and the first interface in a vocabulary; Receiving a first input from a user on a first interface; In response to the first input, matching candidate words from a vocabulary based on a mapping relationship between a character string corresponding to the first input and a character string corresponding to the first interface, and displaying the candidate words; The word library stores at least one keyword and a mapping relationship between each keyword and a corresponding interface. One interface corresponds to a group of mapping relationships. There is a mapping relationship between the candidate word and the first interface.

2. The method according to claim 1, characterized in that: The delimiters include: line break and space.

3. The method according to claim 1, characterized in that The storing the keywords into the vocabulary includes: The keyword and the character string corresponding to the keyword are associated and stored in a word library.

4. The method according to claim 1, characterized in that The extracting keywords from the target text includes: Segment the target text to obtain N candidate segmentations; receiving a second input from a user regarding a target candidate participle among the N candidate participles; In response to the second input, the target candidate word segmentation is used as a keyword.

5. The method according to claim 1 or 3, characterized in that: After extracting the keywords from the target text, the method further includes: Displaying the keywords; receiving a third input of the keyword from a user; The storing of the keywords into the vocabulary includes: In response to the third input, the keyword is stored in a vocabulary.

6. An information recommendation device, characterized in that: The device comprises: an acquisition module, a storage module, a receiving module, a processing module and a display module, wherein: The acquisition module is used to acquire a target text when it is detected that the content inputted in the first interface includes a first symbol; the target text includes: characters between a target character inputted by a user and the first symbol, the target character is: the first character inputted by the user or a second symbol displayed in the first interface before the first symbol; the first symbol and the second symbol are both target symbols; the target symbol includes any one of the following: punctuation marks, separators; The processing module is further used to extract keywords from the target text acquired by the acquisition module; The storage module is further used to store the keywords extracted by the processing module and the mapping relationship between the keywords and the first interface in a vocabulary; The receiving module is used to receive a first input from a user on a first interface; The processing module is configured to match candidate words from a vocabulary based on a mapping relationship between a character string corresponding to the first input and the first interface in response to the first input received by the receiving module; The display module is used to display the candidate words matched by the processing module from the word library; The word library stores at least one keyword and a mapping relationship between each keyword and a corresponding interface. One interface corresponds to a group of mapping relationships. There is a mapping relationship between the candidate word and the first interface.

7. The device according to claim 6, characterized in that The delimiters include: line break and space.

8. The device according to claim 6, characterized in that The storage module is specifically used to associate the keyword with the character string corresponding to the keyword and store them in a vocabulary.

9. The device according to claim 6, characterized in that The processing module is specifically used to segment the target text to obtain N candidate segmentations; The receiving module is further used to receive a second input from a user regarding a target candidate participle among the N candidate participles obtained by the processing module; The processing module is specifically configured to use the target candidate segmented word as a keyword in response to the second input received by the receiving module.

10. The device according to claim 6 or 8, characterized in that The display module is further used to display the keywords; The receiving module is further configured to receive a third input from a user on the keywords displayed by the display module; The storage module is specifically configured to store the keyword into a vocabulary in response to the third input received by the receiving module.

11. An electronic device, characterized in that: The method comprises a processor, a memory, and a program or instruction stored in the memory and executable on the processor, wherein the program or instruction, when executed by the processor, implements the steps of the information recommendation method according to any one of claims 1 to 5.

12. A computer-readable storage medium, characterized in that: The readable storage medium stores a program or instruction, and when the program or instruction is executed by a processor, the steps of the information recommendation method according to any one of claims 1 to 5 are implemented.

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