A vocabulary management method and device

Abstract

The present invention discloses a vocabulary management method, comprising: obtaining at least one hot word and associated words related to the hot word based on the content input by a first user; adding the hot word and the associated words to a preset vocabulary, so that when a second user inputs the hot word, the associated words can be extracted from the preset vocabulary, and the associated words are used as candidates for the hot word. The present invention realizes the technical effect of conveniently and quickly collecting and sorting hot words and related associated words, with high efficiency and less prone to omissions. At the same time, the present invention also discloses a vocabulary management device.

Description

Technical Field

[0001] The present invention relates to the technical field of input methods, and in particular to a vocabulary management method and device. Background Art

[0002] Input method refers to the encoding method used to input various symbols into computers or other devices (such as mobile phones). It is the product of the development of text productivity to a certain stage. Nowadays, people often use input methods when using terminal devices such as mobile phones or tablets. The application of input methods has greatly improved the speed of users inputting text.

[0003] At present, for some hot events related input, it is usually necessary to manually collect and sort out hot words and related associated words, and send them to the input method client. However, this manual method is very inconvenient, inefficient, and prone to omissions. Summary of the invention

[0004] The embodiment of the present application provides a vocabulary management method and device, which solves the technical problem in the prior art that hot words and related associative words need to be obtained manually, which is inefficient and prone to omissions. It achieves the technical effect of conveniently and quickly collecting and organizing hot words and related associative words, which is highly efficient and not prone to omissions.

[0005] In the first aspect, the present application provides the following technical solutions through an embodiment of the present application:

[0006] A vocabulary management method, comprising:

[0007] Based on the content input by the first user, obtaining at least one hot word and associated words related to the hot word;

[0008] The hot word and the associated word are added to a preset word library, so that when a second user inputs the hot word, the associated word can be extracted from the preset word library and used as a candidate word for the hot word.

[0009] Preferably, the step of obtaining at least one hot word and associated words related to the hot word based on the content input by the first user includes:

[0010] Based on the content input by the first user, hot word mining is performed to obtain at least one hot word;

[0011] Based on the hot words, associative words related to the hot words are mined.

[0012] Preferably, the hot word mining based on the content input by the first user to obtain at least one hot word includes:

[0013] The first input operations of all network users or preset group users are counted to obtain the first words input by all network users and the first input frequency corresponding to each first word, and the first words whose first input frequency is greater than or equal to the first preset frequency are used as the hot words.

[0014] Preferably, mining out associated words related to the hot words based on the hot words includes:

[0015] Counting the second words input after the hot word by users of the entire network or a preset group of users, and the second input frequency corresponding to each second word, and taking the second words with a second input frequency greater than or equal to a second preset frequency as associated words related to the hot word; or

[0016] The hot words are used as search keywords and searched using a search engine to obtain articles related to the hot events corresponding to the hot words, and associated words related to the hot words are determined in the titles or texts of the articles.

[0017] Preferably, after adding the hot words and the associated words to the preset word library, the method further includes:

[0018] Determine whether the hot word is within the validity period;

[0019] If not, the hot words and the associated words are invalidated.

[0020] Preferably, the determining whether the hot word is within the validity period includes:

[0021] Obtaining a third input frequency of the hot word recently input by all network users or a preset group of users;

[0022] Determining whether the third input frequency is greater than or equal to a third preset frequency;

[0023] If so, the hot word is within the validity period;

[0024] Otherwise, the hot word is not within the validity period.

[0025] Preferably, the invalidation processing of the hot words and the associated words includes:

[0026] The hot words and the associated words are deleted from the preset word library.

[0027] In the second aspect, the present application provides the following technical solution through an embodiment of the present application:

[0028] A vocabulary management device, comprising:

[0029] An obtaining unit, configured to obtain at least one hot word and associated words related to the hot word based on the content input by the first user;

[0030] The adding unit is used to add the hot word and the associated word to a preset word library, so that when the second user inputs the hot word, the associated word can be extracted from the preset word library and output as a candidate word of the hot word.

[0031] Preferably, the obtaining unit comprises:

[0032] A first mining subunit is used to mine hot words based on the content input by the first user to obtain at least one hot word;

[0033] The second mining sub-unit is used to mine associated words related to the hot word based on the hot word.

[0034] Preferably, the first sub-mining unit is specifically used for:

[0035] The first words input by all network users or a preset group of users and the first input frequency corresponding to each first word are counted, and the first words whose first input frequency is greater than or equal to the first preset frequency are taken as the hot words.

[0036] Preferably, the second mining subunit is specifically used for:

[0037] Counting the second words input after the hot word by users of the entire network or a preset group of users, and the second input frequency corresponding to each second word, and taking the second words with a second input frequency greater than or equal to a second preset frequency as associated words related to the hot word; or

[0038] The hot words are used as search keywords and searched using a search engine to obtain articles related to the hot events corresponding to the hot words, and associated words related to the hot words are determined in the titles or texts of the articles.

[0039] Preferably, the vocabulary management device further includes:

[0040] A judging unit, configured to judge whether the hot word is within the validity period after the hot word and the associated word are added to the preset word library;

[0041] The invalidation unit is used for invalidating the hot words and the associated words if no.

[0042] Preferably, the judging unit is specifically used for:

[0043] Obtain the third input frequency of the hot word recently input by all network users or preset group users; determine whether the third input frequency is greater than or equal to the third preset frequency; if so, the hot word is within the validity period; otherwise, the hot word is not within the validity period.

[0044] Preferably, the failure unit is specifically used for:

[0045] The hot words and the associated words are deleted from the preset word library.

[0046] In a third aspect, the present application provides the following technical solutions through an embodiment of the present application:

[0047] A vocabulary management device includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the following steps when executing the program:

[0048] Based on the content input by the first user, at least one hot word and an associated word related to the hot word are obtained; the hot word and the associated word are added to a preset word library, so that when a second user inputs the hot word, the associated word can be extracted from the preset word library and output as a candidate word for the hot word.

[0049] In a fourth aspect, the present application provides the following technical solutions through an embodiment of the present application:

[0050] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements the following steps:

[0051] Based on the content input by the first user, at least one hot word and an associated word related to the hot word are obtained; the hot word and the associated word are added to a preset word library, so that when a second user inputs the hot word, the associated word can be extracted from the preset word library and used as a candidate word for the hot word.

[0052] One or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages:

[0053] In an embodiment of the present invention, a vocabulary management method is disclosed, including: based on the content input by the first user, obtaining at least one hot word and associated words related to the hot word; adding the hot word and the associated words to a preset vocabulary, so that when the second user inputs the hot word, the associated words can be extracted from the preset vocabulary, and the associated words are used as candidates for the hot word. Since at least one hot word and associated words related to the hot word are obtained based on the content input by the first user, there is no need to manually edit the hot word and the associated words, which is more convenient and quick. Therefore, the technical problem that the hot word and the associated words need to be obtained manually in the prior art, which is inefficient and easy to cause omissions, is effectively solved, and the technical effect of conveniently and quickly collecting and sorting the hot words and the associated words is achieved, which is efficient and not easy to cause omissions. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0055] Figure 1 A flowchart of a library management method according to an embodiment of the present invention;

[0056] Figure 2 A schematic diagram of the structure of a library management device in an embodiment of the present invention;

[0057] Figure 3 A schematic diagram of the structure of a library management device in an embodiment of the present invention;

[0058] Figure 4 It is a structural diagram of a vocabulary management device used as a server in an embodiment of the present invention. DETAILED DESCRIPTION

[0059] The embodiment of the present application provides a vocabulary management method and device, which solves the technical problem in the prior art that hot words and related associative words need to be obtained manually, which is inefficient and prone to omissions. It achieves the technical effect of conveniently and quickly collecting and organizing hot words and related associative words, which is highly efficient and not prone to omissions.

[0060] The technical solution of the embodiment of the present application is to solve the above technical problems, and the overall idea is as follows:

[0061] A vocabulary management method includes: obtaining at least one hot word and an associated word related to the hot word based on content input by a first user; adding the hot word and the associated word to a preset vocabulary, so that when a second user inputs the hot word, the associated word can be extracted from the preset vocabulary and output as a candidate word for the hot word.

[0062] In order to better understand the above technical solution, the above technical solution will be described in detail below in conjunction with the accompanying drawings and specific implementation methods.

[0063] First of all, the term "and / or" in this article is only a description of the association relationship of the associated objects, indicating that there can be three relationships. For example, A and / or B can mean: A exists alone, A and B exist at the same time, and B exists alone. In addition, the character " / " in this article generally indicates that the associated objects before and after are in an "or" relationship.

[0064] Embodiment 1

[0065] like Figure 1 As shown, this embodiment provides a vocabulary management method, including:

[0066] Step S101: based on the content input by the first user, obtaining at least one hot word and associated words related to the hot word.

[0067] In the specific implementation process, the so-called "hot words" refer to words with high popularity, that is, words that are frequently used by users recently. On the input method client side, hot words are words that are frequently input by users. The generation of hot words is often related to recent hot events (for example, the last 12 hours, or the last 24 hours, or the last 48 hours, or the last 72 hours, or the last week, etc.). Due to the sudden occurrence of a hot event, the attention of users (for example, all network users) to the hot event has increased sharply, which in turn has led to a surge in the frequency of users inputting words related to the hot event (i.e., hot words) recently.

[0068] As an optional embodiment, step S101 includes:

[0069] Based on the content input by the first user, hot word mining is performed to obtain at least one hot word; based on the hot word, associative words related to the hot word are mined.

[0070] In the specific implementation process, hot words can be mined based on the content input by the first user, wherein the first user may be multiple users using the above-mentioned input method client (for example: a preset group of users or users of the entire network). Here, the more first users there are, the better, and this embodiment does not make any specific limitations.

[0071] The “entire network of users” may be: a large number of users using the above input method client. The more users the better. Preferably, it refers to all users using the input method client.

[0072] The "preset group of users" refers to: a preset group of users with certain common characteristics, for example, users in the same city, or users of the same age group, or users with the same usage habits, or users with the same hobbies, and so on.

[0073] As an optional embodiment, performing hot word mining based on the content input by the first user to obtain at least one hot word includes:

[0074] The first words input by all network users (or preset group users) and the first input frequency corresponding to each first word are counted, and the first words whose first input frequency is greater than the first preset frequency are taken as hot words.

[0075] In the specific implementation process, for the input method client used by each user in the entire network (or a preset group of users), the input operation (i.e., the second input operation) information of the corresponding user in the recent period (e.g., the last 12 hours, the last 24 hours, the last 48 hours, the last 72 hours, the last week, etc.) can be uploaded to the server, and the server determines the vocabulary recently input by each user based on the input operation of each user; or, the input method client directly uploads each vocabulary recently input by each user to the server. Further, the server counts the frequency of each vocabulary recently input by users in the entire network (i.e., the second input frequency), and determines the vocabulary with an input frequency greater than the first preset frequency as a hot word.

[0076] For example, the "McDonald's renamed Golden Arches" event is a recent hot event. Netizens pay great attention to this event and often input relevant information about this event. At this time, the server counts that the frequency of "McDonald's" input by users across the network has increased significantly recently. In the past, the frequency of "McDonald's" input by users across the network was less than 500,000 times / day, but recently, the frequency of "McDonald's" input by users across the network has exceeded 5 million times / day. Here, the first preset frequency can be set to 1 million times / day. The server counts the frequency of "McDonald's" input by users across the network recently (for example, 5 million times / day), and finds that it is greater than the first preset frequency (1 million times / day), so it can be determined that "McDonald's" is a recent hot word.

[0077] In the specific implementation process, the first preset frequency can be flexibly set according to actual conditions and is not specifically limited here.

[0078] In the specific implementation process, the server can count the average input frequency of each word by users of the entire network within a preset time period (for example: half a year or a year), and the average frequency can reflect the degree of attention paid to each word by users in the "normal period". Further, the first preset frequency can be set to W times (for example: 1.5 times, or 2 times, or 3 times, etc.) the average input frequency of each word (W is positive). If the input frequency of a certain word recently input by users of the entire network is greater than the first preset frequency, this is most likely caused by a hot event. At this time, the word is in the "hot period", and it can be determined that the word is a recent hot word. In the specific implementation process, after the server mines out hot words based on the content that has been input by users of the entire network (or preset group users), it can further mine out associated words related to the hot word.

[0079] As an optional embodiment, mining out associated words related to the hot word based on the hot word includes:

[0080] Count the second words input by all network users (or preset group users) after the hot word, and the second input frequency corresponding to each second word, and take the second words whose second input frequency is greater than or equal to the second preset frequency as associated words related to the hot word; or

[0081] Use the hot words as search keywords and use search engines to search for articles related to the hot events corresponding to the hot words, and identify the associated words related to the hot words in the title or body of the article.

[0082] In the specific implementation process, the server can collect statistics on the input behaviors of all network users (or preset group users), obtain the words (i.e., the second words) that the users input immediately after inputting the hot words, and obtain the input frequency of the words. If the input frequency of the words (i.e., the second input frequency) is greater than the second preset frequency, it can be determined that the words are associated words related to the hot words. The associated words include binary associated words, ternary associated words, and so on.

[0083] For example, take the "McDonald's changed its name to Golden Arches" event as an example. After the event became a recent hot topic, the probability of users entering "change name" immediately after entering "McDonald's Old McDonald" increased significantly. In the past, the frequency of users entering "change name" was less than 500,000 times / day, while recently, users across the entire network entered "change name" more than 5 million times / day. Here, the second preset frequency can be set to 1 million times / day. The server obtains the frequency of users across the entire network entering "change name" recently (for example, 5 million times / day). If it is greater than the second preset frequency (1 million times / day), it can be determined that "change name" is an associative word of "McDonald's". Similarly, further analysis can be conducted to find out that "Golden Arches" is also an associative word of "McDonald's".

[0084] Among them, "binary associative words" refer to two words input continuously during the user input process, such as: "McDonald's#Change name"; when performing "binary association" later, when the user inputs "McDonald's", the input method client can automatically associate the word "Change name" based on the above binary associative word information "McDonald's#Change name".

[0085] Among them, "ternary associative words" refer to three words entered consecutively by the user during the input process, such as: "McDonald's#change name#Golden Arches"; when performing "ternary association" later, after the user enters the two words "McDonald's" + "change name", the input method client can automatically associate the word "Golden Arches" based on the above ternary associative word information "McDonald's#change name#Golden Arches".

[0086] In a specific implementation process, the second preset frequency may be the same as the first preset frequency, or may be different.

[0087] In the specific implementation process, the mined hot words can also be used as search keywords, and search engines (such as "Sogou" search, "Baidu" search, "Google" search, etc.) can be used to search on the Internet to search for relevant articles on the hot events corresponding to the hot words, and further mine associative words related to the hot words in the title or text of the article.

[0088] For example, after finding out that "McDonald's" is a recent hot word, you can use "McDonald's" as a search keyword to search on the Internet, and sort the search results in descending order of the click rate of the search results to obtain the top N search results, where N is a positive integer. Then visit the web pages corresponding to the N search results respectively. If the page content is an article, then according to the title or body of the article, the words near the hot word "McDonald's" (for example, the first word after "change of name", or the second word after "Golden Arches") are used as the associated words of "McDonald's".

[0089] Step S102: adding the hot word and the associated word to a preset word library, so that when the second user inputs the hot word, the associated word can be extracted from the preset word library and used as a candidate word for the hot word.

[0090] In the specific implementation process, after the server mines the hot word and the associated words related to the hot word, it adds the hot word and the associated words to a preset word library, which can be a cloud word library. After that, the server can send the preset word library to the input method client used by each user in the entire network. In this way, after any user in the entire network uses the input method client to input the hot word, the input method client can extract the associated words related to the hot word in the preset word library and output the associated words in the candidate area of ​​the input method interface. The associated words are the candidate words of the hot word.

[0091] For example, after a user inputs "McDonald's", the input method client extracts the associated words "change name" and "Golden Arches" related to "McDonald's" from the preset word library, and outputs the candidate words "change name" and "Golden Arches" in the candidate area of ​​the input method interface. Among them, when performing "binary association", when the user inputs "McDonald's", the input method client can automatically associate the word "change name" according to the above binary association word information "McDonald's#change name"; when performing "ternary association", after the user inputs the two words "McDonald's" + "change name", the input method client can automatically associate the word "Golden Arches" according to the above ternary association word information "McDonald's#change name#Golden Arches". In this way, if the user wants to enter "change name" or "Golden Arches", he can directly select the desired candidate word in the candidate area, which is convenient and quick.

[0092] In the specific implementation process, the server can regularly update the preset word library, obtain the latest hot words and their associated words, and send the latest preset word library to the input method client used by each user in the entire network.

[0093] In this embodiment, at least one hot word and associated words related to the hot word are obtained based on the content input by the first user, so there is no need to manually edit the hot words and associated associated words, which is more convenient and quick. Therefore, the technical problem of manually obtaining hot words and associated associated words in the prior art, which is inefficient and easy to cause omissions, is effectively solved, and the hot words and associated associated words are collected and sorted conveniently and quickly, which is efficient and not easy to cause omissions.

[0094] Further, as an optional embodiment, after step S102, the following steps are further included:

[0095] Determine whether the hot word is within the validity period;

[0096] If not (ie, the hot word is not within the validity period), the hot word and the associated words will be invalidated.

[0097] In the specific implementation process, after a hot event occurs, as time goes by, the user's attention to the hot event will also decrease, and the original hot event will no longer be a hot event. At this time, the hot words related to the event are no longer hot words, and the frequency of inputting hot words and their associated words will also decrease accordingly. Therefore, each hot word can be monitored to determine whether the hot word is within the validity period. If it is, the hot word is retained (for example: the hot word and its associated words are retained in the preset word library). If not, the hot word is invalidated. After a hot word is invalidated, if the user enters the hot word again, the associated words of the hot word will no longer be output as candidate words.

[0098] As an optional embodiment, the determining whether the hot word is within the validity period includes:

[0099] Obtain the third input frequency of the hot word recently input by all network users (or preset group users); determine whether the third input frequency is greater than or equal to the third preset frequency; if greater than or equal to, the hot word is within the validity period; otherwise, the hot word is not within the validity period. The third preset frequency may be the same as or different from the first preset frequency mentioned above.

[0100] During the specific implementation process, the server can monitor the popularity of each hot word in real time. If it is found that the input frequency of a hot word by users of the entire network (or a preset group of users) (i.e., the third input frequency) is lower than the third preset frequency (for example, falling back to the average input frequency of the "normal period"), it is determined that the hot word is not within the validity period, and the hot word is invalidated; if it is found that the input frequency of the hot word is greater than or equal to the third preset frequency, the hot word and its associated words are retained in the preset vocabulary.

[0101] As an optional embodiment, the invalidation processing of the hot words and the associated words includes: deleting the hot words and the associated words from a preset word library.

[0102] In the specific implementation process, the so-called "invalidation processing" is to delete the hot words and their associated words that are no longer valid from the preset word library, which can reduce the size of the preset word library and ensure that the preset word library is concise and practical. In addition, since the original hot words are no longer hot words, the frequency of the associated words of the hot words in the preset word library being input by users will also be greatly reduced. If the associated words continue to be output as candidate words, it will cause interference to users and also reduce the success rate of candidate word recommendation. Here, deleting the hot words and their associated words that are no longer valid from the preset word library can avoid unnecessary interference to users and improve the success rate of recommending candidate words.

[0103] For example, if "McDonald's" is no longer valid, it means that "McDonald's" is no longer a hot word, so "McDonald's" and its associated words "change name" and "Golden Arches" are deleted from the preset vocabulary.

[0104] The technical solutions in the above embodiments of the present application have at least the following technical effects or advantages:

[0105] In an embodiment of the present invention, a vocabulary management method is disclosed, including: based on the content input by the first user, obtaining at least one hot word and associated words related to the hot word; adding the hot word and the associated words to a preset vocabulary, so that when the second user inputs the hot word, the associated words can be extracted from the preset vocabulary, and the associated words are used as candidates for the hot word. Since at least one hot word and associated words related to the hot word are obtained based on the content input by the first user, there is no need to manually edit the hot word and the associated words, which is more convenient and quick. Therefore, the technical problem that the hot word and the associated words need to be obtained manually in the prior art, which is inefficient and easy to cause omissions, is effectively solved, and the technical effect of conveniently and quickly collecting and sorting the hot words and the associated words is achieved, which is efficient and not easy to cause omissions.

[0106] Embodiment 2

[0107] Based on the same inventive concept, Figure 2 As shown, this embodiment provides a vocabulary management device, including:

[0108] The obtaining unit 201 is used to obtain at least one hot word and associated words related to the hot word based on the content input by the first user;

[0109] The adding unit 202 is used to add the hot word and the associated word to a preset word library, so that when the second user inputs the hot word, the associated word can be extracted from the preset word library and output as a candidate word of the hot word.

[0110] As an optional embodiment, the obtaining unit 201 includes:

[0111] A first mining subunit is used to mine hot words based on the content input by the first user to obtain at least one hot word;

[0112] The second mining sub-unit is used to mine associated words related to the hot word based on the hot word.

[0113] As an optional embodiment, the first sub-mining unit is specifically used for:

[0114] The first words input by all network users or a preset group of users and the first input frequency corresponding to each first word are counted, and the first words whose first input frequency is greater than or equal to the first preset frequency are taken as the hot words.

[0115] As an optional embodiment, the second sub-mining unit is specifically used for:

[0116] Counting the second words input after the hot word by users of the entire network or a preset group of users, and the second input frequency corresponding to each second word, and taking the second words with a second input frequency greater than or equal to a second preset frequency as associated words related to the hot word; or

[0117] The hot words are used as search keywords and searched using a search engine to obtain articles related to the hot events corresponding to the hot words, and associated words related to the hot words are determined in the titles or texts of the articles.

[0118] As an optional embodiment, the vocabulary management device further includes:

[0119] A judging unit, configured to judge whether the hot word is within the validity period after the hot word and the associated word are added to the preset word library;

[0120] The invalidation unit is used for invalidating the hot words and the associated words if no.

[0121] As an optional embodiment, the judging unit is specifically configured to:

[0122] Obtain the third input frequency of the hot word recently input by all network users or preset group users; determine whether the third input frequency is greater than or equal to the third preset frequency; if so, the hot word is within the validity period; otherwise, the hot word is not within the validity period.

[0123] As an optional embodiment, the failure unit is specifically used to:

[0124] The hot words and the associated words are deleted from the preset word library.

[0125] Since the word library management device introduced in this embodiment is a device used to implement the word library management method in the embodiment of this application, based on the word library management method introduced in the embodiment of this application, the technical personnel of this field can understand the specific implementation of the electronic device of this embodiment and its various variations, so how the electronic device implements the method in the embodiment of this application is not described in detail here. As long as the electronic device used by the technical personnel of this field to implement the word library management method in the embodiment of this application, it belongs to the scope of protection of this application.

[0126] The technical solutions in the above embodiments of the present application have at least the following technical effects or advantages:

[0127] In an embodiment of the present invention, a vocabulary management device is disclosed, including: an acquisition unit, based on the content input by the first user, to obtain at least one hot word and associated words related to the hot word; an adding unit, used to add the hot word and the associated words to a preset vocabulary, so that when the second user inputs the hot word, the associated words can be extracted from the preset vocabulary, and the associated words are output as candidate words of the hot word. Since at least one hot word and associated words related to the hot word are obtained based on the content input by the first user, it is not necessary to manually edit the hot word and the associated words, which is more convenient and quick. Therefore, the technical problem that the hot word and the associated words need to be obtained manually in the prior art, which is inefficient and easy to cause omissions, is effectively solved, and the technical effect of conveniently and quickly collecting and sorting the hot words and the associated words is achieved, which is efficient and not easy to cause omissions.

[0128] Regarding the vocabulary management device in the above embodiment, the specific manner in which each module performs operations has been described in detail in the embodiment of the method, and will not be elaborated here.

[0129] Figure 3 8 is a block diagram of a vocabulary management device 800 according to an exemplary embodiment. For example, the device 800 may be a mobile phone, a computer, a digital broadcast terminal, a messaging device, a game console, a tablet device, a medical device, a fitness device, a personal digital assistant, etc.

[0130] Reference Figure 3 , the device 800 may include one or more of the following components: a processing component 802 , a memory 804 , a power component 806 , a multimedia component 808 , an audio component 810 , an input / output (I / O) interface 812 , a sensor component 814 , and a communication component 816 .

[0131] The processing component 802 generally controls the overall operation of the device 800, such as operations associated with display, phone calls, data communications, camera operations, and recording operations. The processing component 802 may include one or more processors 820 to execute instructions to complete all or part of the steps of the above-mentioned method. In addition, the processing component 802 may include one or more modules to facilitate the interaction between the processing component 802 and other components. For example, the processing component 802 may include a multimedia module to facilitate the interaction between the multimedia component 808 and the processing component 802.

[0132] The memory 804 is configured to store various types of data to support operations on the device 800. Examples of such data include instructions for any application or method operating on the device 800, contact data, phone book data, messages, pictures, videos, etc. The memory 804 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk or optical disk.

[0133] The power supply component 806 provides power to the various components of the device 800. The power supply component 806 may include a power management system, one or more power supplies, and other components associated with generating, managing, and distributing power for the device 800.

[0134] The multimedia component 808 includes a screen that provides an output interface between the device 800 and the user. In some embodiments, the screen may include a liquid crystal display (LCD) and a touch panel (TP). If the screen includes a touch panel, the screen may be implemented as a touch screen to receive input signals from the user. The touch panel includes one or more touch sensors to sense touch, slide, and gestures on the touch panel. The touch sensor may not only sense the boundaries of the touch or slide action, but also detect the duration and pressure associated with the touch or slide operation. In some embodiments, the multimedia component 808 includes a front camera and / or a rear camera. When the device 800 is in an operating mode, such as a shooting mode or a video mode, the front camera and / or the rear camera may receive external multimedia data. Each front camera and rear camera may be a fixed optical lens system or have a focal length and optical zoom capability.

[0135] The audio component 810 is configured to output and / or input audio signals. For example, the audio component 810 includes a microphone (MIC), and when the device 800 is in an operating mode, such as a call mode, a recording mode, and a speech recognition mode, the microphone is configured to receive an external audio signal. The received audio signal can be further stored in the memory 804 or sent via the communication component 816. In some embodiments, the audio component 810 also includes a speaker for outputting audio signals.

[0136] I / O interface 812 provides an interface between processing component 802 and peripheral interface modules, such as keyboards, click wheels, buttons, etc. These buttons may include but are not limited to: home button, volume button, start button, and lock button.

[0137] The sensor assembly 814 includes one or more sensors for providing various aspects of status assessment for the device 800. For example, the sensor assembly 814 can detect the open / closed state of the device 800, the relative positioning of components, such as the display and keypad of the device 800, and the sensor assembly 814 can also detect the position change of the device 800 or a component of the device 800, the presence or absence of user contact with the device 800, the orientation or acceleration / deceleration of the device 800, and the temperature change of the device 800. The sensor assembly 814 may include a proximity sensor configured to detect the presence of a nearby object without any physical contact. The sensor assembly 814 may also include an optical sensor, such as a CMOS or CCD image sensor, for use in imaging applications. In some embodiments, the sensor assembly 814 may also include an accelerometer, a gyroscope sensor, a magnetic sensor, a pressure sensor, or a temperature sensor.

[0138] The communication component 816 is configured to facilitate wired or wireless communication between the device 800 and other devices. The device 800 can access a wireless network based on a communication standard, such as WiFi, 2G or 3G, or a combination thereof. In an exemplary embodiment, the communication component 816 receives a broadcast signal or broadcast-related information from an external broadcast management system via a broadcast channel. In an exemplary embodiment, the communication component 816 also includes a near field communication (NFC) module to facilitate short-range communication. For example, the NFC module can be implemented based on radio frequency identification (RFID) technology, infrared data association (IrDA) technology, ultra-wideband (UWB) technology, Bluetooth (BT) technology and other technologies.

[0139] In an exemplary embodiment, the apparatus 800 may be implemented by one or more application specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field programmable gate arrays (FPGAs), controllers, microcontrollers, microprocessors or other electronic components to perform the above method.

[0140] In an exemplary embodiment, a non-transitory computer-readable storage medium including instructions is also provided, such as a memory 804 including instructions, and the instructions can be executed by the processor 820 of the device 800 to perform the above method. For example, the non-transitory computer-readable storage medium can be a ROM, a random access memory (RAM), a CD-ROM, a magnetic tape, a floppy disk, an optical data storage device, etc.

[0141] A non-temporary computer-readable storage medium, when the instructions in the storage medium are executed by a processor of a mobile terminal, enables the mobile terminal to execute a vocabulary management method, the method comprising: obtaining at least one hot word and an associated word related to the hot word based on content input by a first user; adding the hot word and the associated word to a preset vocabulary, so that when a second user inputs the hot word, the associated word can be extracted from the preset vocabulary and output as a candidate word for the hot word.

[0142] Figure 4 1 is a schematic diagram of the structure of the word library management device as a server in an embodiment of the present invention. The server 1900 may have relatively large differences due to different configurations or performances, and may include one or more central processing units (CPU) 1922 (for example, one or more processors) and memory 1932, and one or more storage media 1930 (for example, one or more mass storage devices) storing application programs 1942 or data 1944. Among them, the memory 1932 and the storage medium 1930 can be short-term storage or permanent storage. The program stored in the storage medium 1930 may include one or more modules (not shown in the figure), and each module may include a series of instruction operations in the server. Furthermore, the central processing unit 1922 can be configured to communicate with the storage medium 1930 to execute a series of instruction operations in the storage medium 1930 on the server 1900.

[0143] The server 1900 may also include one or more power supplies 1926, one or more wired or wireless network interfaces 1950, one or more input and output interfaces 1958, one or more keyboards 1956, and / or, one or more operating systems 1941, such as Windows ServerTM, Mac OS XTM, UnixTM, LinuxTM, FreeBSDTM, etc.

[0144] Those skilled in the art will readily appreciate other embodiments of the invention after considering the specification and practicing the invention disclosed herein. The present invention is intended to cover any variations, uses or adaptations of the present invention that follow the general principles of the present invention and include common knowledge or customary techniques in the art that are not disclosed in this disclosure. The description and examples are to be considered exemplary only, and the true scope and spirit of the present invention are indicated by the following claims.

[0145] It should be understood that the present invention is not limited to the precise structure described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from the scope thereof. The scope of the present invention is limited only by the appended claims. The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modification, equivalent substitution, improvement, etc. made within the spirit and principle of the present invention shall be included in the scope of protection of the present invention.

Claims

1. A vocabulary management method, characterized in that: include: Counting the first words input by the first user and the first input frequency corresponding to each first word, taking the first words whose first input frequency is greater than or equal to the first preset frequency as hot words, the ratio between the first preset frequency and the average input frequency is a preset value, and the average input frequency reflects the attention degree of the first user to the first word in a non-hotspot period; the first user is a user of the entire network or a preset group of users; Counting the second words input by the first user after the hot word and the second input frequency corresponding to each second word, and taking the second words whose second input frequency is greater than or equal to the second preset frequency as the associated words related to the hot word; the associated words include binary associated words and ternary associated words, the binary associated words are two words input continuously during the user input process, and the ternary associated words are three words input continuously during the user input process; Adding the hot word and the associated word to a preset word library, so that when a second user inputs the hot word, the input method client used by the second user can extract at least one of the binary associated word and the ternary associated word from the preset word library through at least one of binary association and ternary association, and use at least one of the binary associated word and the ternary associated word as a candidate word for the hot word; Acquire a third input frequency of the hot word input by the first user within a preset time period; If the third input frequency is less than the third preset frequency, it is determined that the hot word is not within the validity period, and the hot word and the associated word corresponding to the hot word are deleted from the preset word library.

2. The vocabulary management method according to claim 1, characterized in that: The method further comprises: Determining whether the third input frequency is greater than or equal to the third preset frequency; If so, the hot word is within the validity period.

3. A vocabulary management device, characterized in that: include: The obtaining unit includes a first excavation subunit and a second excavation subunit; The first mining sub-unit is used to count the first words input by the first user and the first input frequency corresponding to each first word, and take the first words whose first input frequency is greater than or equal to the first preset frequency as hot words, the ratio between the first preset frequency and the average input frequency is a preset value, and the average input frequency reflects the attention degree of the first user to the first word in a non-hot period; the first user is a user of the entire network or a preset group of users; The second mining subunit is used to count the second words input by the first user after the hot word, and the second input frequency corresponding to each second word, and use the second words whose second input frequency is greater than or equal to the second preset frequency as the associated words related to the hot word; the associated words include bigram associated words and trigram associated words, the bigram associated words are two words input continuously during the user input process, and the trigram associated words are three words input continuously during the user input process; an adding unit, configured to add the hot word and the associative word to a preset word library, so that when a second user inputs the hot word, the input method client used by the second user can extract at least one of the binary associative word and the ternary associative word from the preset word library through at least one of binary association and ternary association, and use at least one of the binary associative word and the ternary associative word as a candidate word for the hot word; A judgment unit, used for obtaining a third input frequency of the hot word input by the first user within a preset time period; If the third input frequency is less than the third preset frequency, it is determined that the hot word is not within the validity period; The invalidation unit is used to delete the hot word and the associated word corresponding to the hot word from the preset word library.

4. The word library management device according to claim 3, characterized in that: The judging unit is further specifically used for: Determine whether the third input frequency is greater than or equal to the third preset frequency; if so, the hot word is within the validity period.

5. A vocabulary management device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the following steps are implemented: Counting the first words input by the first user and the first input frequency corresponding to each first word, taking the first words whose first input frequency is greater than or equal to the first preset frequency as hot words, the ratio between the first preset frequency and the average input frequency is a preset value, and the average input frequency reflects the attention degree of the first user to the first word in a non-hotspot period; the first user is a user of the entire network or a preset group of users; Counting the second words input by the first user after the hot word and the second input frequency corresponding to each second word, and taking the second words whose second input frequency is greater than or equal to the second preset frequency as the associated words related to the hot word; the associated words include binary associated words and ternary associated words, the binary associated words are two words input continuously during the user input process, and the ternary associated words are three words input continuously during the user input process; Adding the hot word and the associated word to a preset word library, so that when a second user inputs the hot word, the input method client used by the second user can extract at least one of the binary associated word and the ternary associated word from the preset word library through at least one of binary association and ternary association, and use at least one of the binary associated word and the ternary associated word as a candidate word for the hot word; Acquire a third input frequency of the hot word input by the first user within a preset time period; If the third input frequency is less than the third preset frequency, it is determined that the hot word is not within the validity period, and the hot word and the associated word corresponding to the hot word are deleted from the preset word library.

6. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the following steps are implemented: Counting the first words input by the first user and the first input frequency corresponding to each first word, taking the first words whose first input frequency is greater than or equal to the first preset frequency as hot words, the ratio between the first preset frequency and the average input frequency is a preset value, and the average input frequency reflects the attention degree of the first user to the first word in a non-hotspot period; the first user is a user of the entire network or a preset group of users; Counting the second words input by the first user after the hot word and the second input frequency corresponding to each second word, and taking the second words whose second input frequency is greater than or equal to the second preset frequency as the associated words related to the hot word; the associated words include binary associated words and ternary associated words, the binary associated words are two words input continuously during the user input process, and the ternary associated words are three words input continuously during the user input process; Adding the hot word and the associated word to a preset word library, so that when a second user inputs the hot word, the input method client used by the second user can extract at least one of the binary associated word and the ternary associated word from the preset word library through at least one of binary association and ternary association, and use at least one of the binary associated word and the ternary associated word as a candidate word for the hot word; Acquire a third input frequency of the hot word input by the first user within a preset time period; If the third input frequency is less than the third preset frequency, it is determined that the hot word is not within the validity period, and the hot word and the associated word corresponding to the hot word are deleted from the preset word library.

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