CN109521888B

CN109521888B - Input method, device and medium

Info

Publication number: CN109521888B
Application number: CN201710848202.5A
Authority: CN
Inventors: 左艳波
Original assignee: Beijing Sogou Technology Development Co Ltd
Current assignee: Beijing Sogou Technology Development Co Ltd
Priority date: 2017-09-19
Filing date: 2017-09-19
Publication date: 2022-11-01
Anticipated expiration: 2037-09-19
Also published as: CN109521888A

Abstract

The embodiment of the invention provides an input method, an input device and a medium, wherein the input method specifically comprises the following steps: determining the weight corresponding to the word frequency of the candidate item corresponding to the input string of the user under the historical input environment characteristics according to the matching degree between the current input environment characteristics and the historical input environment characteristics corresponding to the input string of the user; the word frequency of the candidate item under the historical input environment characteristics is obtained according to historical input behavior data of a user, and the historical input behavior data comprises: the method comprises the steps of displaying screen content and corresponding historical input environment characteristics; according to the weight, carrying out weighting processing on the word frequency of the candidate item under at least one historical input environment characteristic to obtain a target word frequency corresponding to the candidate item; and sorting the candidate items according to the target word frequency corresponding to the candidate items. The embodiment of the invention can enable the sorting result of the candidate items to better accord with the input intention corresponding to the current input environment characteristic, thereby improving the input efficiency of the user.

Description

Input method, device and medium

Technical Field

The present invention relates to the field of input methods, and in particular, to an input method, an input device, a device for input, and a machine-readable medium.

Background

With the popularization and development of computer technology and internet technology, input method programs have become important tools for users to interact with computers. Users in different professional fields, different interests and use habits have higher and higher requirements on the intelligence of input method programs.

In the input process of the existing input method program, the word frequency of the corresponding entry in the word stock can be updated according to the on-screen word of the user, so that the on-screen word can be ranked at a position closer to the front in the candidate items in the subsequent input process, and the user can conveniently select the on-screen word.

In practical applications, users often have different input intentions in different input environments. For example, for the input string "lyq", in the input context of the e-commerce platform, the user's input intent may be "dress"; in the input environment of the travel platform, the input intention of the user may be "travel area"; in the input context of a search engine, the user's input intent may be "router" or the like.

However, the existing input method programs usually rank the candidate items according to the word frequency of the entry in the word library, and the ranking result of the candidate items cannot meet the input intention corresponding to the current input environment. For example, for the input string "lyq", the existing input method program generally ranks the candidates corresponding to the input string "lyq" according to the word frequency, and under different input environments such as an e-commerce platform, a travel platform, or a search engine, the ranking results of the candidates provided by the existing input method program are often consistent, so that the ranking results of the candidates cannot be changed along with the change of the input intention corresponding to the current input environment.

Disclosure of Invention

Embodiments of the present invention provide an input method, an input apparatus, an apparatus for input, and a machine-readable medium, which can make a ranking result of candidate items better conform to an input intention corresponding to a current input environment characteristic, thereby improving input efficiency of a user.

In order to solve the above problem, an embodiment of the present invention discloses an input method, including:

determining the weight corresponding to the word frequency of the candidate item corresponding to the input string of the user under the historical input environment characteristics according to the matching degree between the current input environment characteristics and the historical input environment characteristics corresponding to the input string of the user; the word frequency of the candidate under the characteristic of the historical input environment is obtained according to historical input behavior data of a user, and the historical input behavior data comprises the following steps: the method comprises the steps of (1) displaying contents and corresponding historical input environment characteristics;

according to the weight, carrying out weighting processing on the word frequency of the candidate item under at least one historical input environment characteristic to obtain a target word frequency corresponding to the candidate item;

and sorting the candidate items according to the target word frequency corresponding to the candidate items.

Optionally, the matching degree between the current input environmental feature and the historical input environmental feature includes: a degree of correlation between the current input environmental characteristics and the historical input environmental characteristics.

Optionally, the correlation between the current input environmental characteristic and the historical input environmental characteristic is obtained according to historical input behavior data of the user under the current input environmental characteristic and the historical input environmental characteristic, respectively.

Optionally, the correlation between the current input environmental characteristics and the historical input environmental characteristics is obtained according to the co-occurrence frequency of the content on the screen under the current input environmental characteristics and the historical input environmental characteristics.

Optionally, the determining a weight corresponding to a word frequency of a candidate item corresponding to the input string of the user under the historical input environment characteristics includes:

and determining the weight corresponding to the word frequency of the candidate item corresponding to the input string of the user under the historical input environmental characteristics according to the matching degree between the current input environmental characteristics and the historical input environmental characteristics, the historical screen-up time of the entry corresponding to the candidate item and/or the word frequency of the candidate item under the historical input environmental characteristics.

Optionally, the current input environment feature and/or the historical input environment feature comprises: at least one of a temporal environment feature, a location environment feature, a climate environment feature, an application environment feature, and a page environment feature.

Optionally, the method further comprises:

collecting historical input behavior data of a user; the historical input behavior data comprises: the method comprises the steps of displaying screen content and corresponding historical input environment characteristics;

and establishing and storing a mapping relation among the entries, the historical input environment characteristics and the word frequency according to the historical input behavior data.

In another aspect, an embodiment of the present invention discloses an input device, including:

the weight determining module is used for determining the weight corresponding to the word frequency of the candidate item corresponding to the input string of the user under the historical input environment characteristics according to the matching degree between the current input environment characteristics and the historical input environment characteristics corresponding to the input string of the user; the word frequency of the candidate item under the historical input environment characteristics is obtained according to historical input behavior data of a user, and the historical input behavior data comprises: the method comprises the steps of displaying screen content and corresponding historical input environment characteristics;

the weighting processing module is used for weighting the word frequency of the candidate item under at least one historical input environment characteristic according to the weight so as to obtain a target word frequency corresponding to the candidate item; and

and the ranking display module is used for ranking and displaying the candidate items according to the target word frequency corresponding to the candidate items.

Optionally, the matching degree between the current input environmental feature and the historical input environmental feature includes: a degree of correlation between the current input environmental characteristic and the historical input environmental characteristic.

Optionally, the weight determining module includes:

and the weight determining submodule is used for determining the weight corresponding to the word frequency of the candidate item corresponding to the input string of the user under the historical input environmental characteristics according to the matching degree between the current input environmental characteristics and the historical input environmental characteristics, the historical screen-up time of the candidate item corresponding to the entry and/or the word frequency of the candidate item under the historical input environmental characteristics.

Optionally, the apparatus further comprises:

the collection module is used for collecting historical input behavior data of a user; the historical input behavior data comprises: the method comprises the steps of displaying screen content and corresponding historical input environment characteristics;

and the mapping establishment storage module is used for establishing and storing the mapping relation among the entries, the historical input environment characteristics and the word frequency according to the historical input behavior data.

In yet another aspect, an embodiment of the present invention discloses an apparatus for input, comprising a memory, and one or more programs, wherein the one or more programs are stored in the memory, and configured to be executed by the one or more processors comprises instructions for:

determining the weight corresponding to the word frequency of the candidate item corresponding to the input string of the user under the historical input environmental characteristics according to the matching degree between the current input environmental characteristics and the historical input environmental characteristics corresponding to the input string of the user; the word frequency of the candidate item under the historical input environment characteristics is obtained according to historical input behavior data of a user, and the historical input behavior data comprises: the method comprises the steps of displaying screen content and corresponding historical input environment characteristics;

and sorting and displaying the candidate items according to the target word frequency corresponding to the candidate items.

In yet another aspect, embodiments of the invention disclose one or more machine-readable media having instructions stored thereon, which when executed by one or more processors, cause an apparatus to perform one or more of the aforementioned input methods.

The embodiment of the invention has the following advantages:

the embodiment of the invention performs weighting processing on the word frequency of the candidate item under the historical input environmental characteristic, wherein in the weighting processing process, the weight can be obtained according to the matching degree between the current input environmental characteristic and the historical input environmental characteristic, so the matching degree or the proximity between the word frequency of the candidate item under a certain historical input environmental characteristic and the input intention corresponding to the current input environmental characteristic can be reflected through the weight, and thus, the word frequency under the historical input environmental characteristic closer to the input intention corresponding to the current input environmental characteristic can be increased through the weighting processing of the embodiment of the invention, and therefore, the candidate item is ranked according to the target word frequency obtained through the weighting processing, the ranking result of the candidate item can better accord with the input intention corresponding to the current input environmental characteristic, and the input efficiency of a user can be improved.

Drawings

In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the description of the embodiments of the present invention will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained according to these drawings without inventive labor.

FIG. 1 is a flow chart of steps of an embodiment of a method for processing a lexicon according to the present invention;

FIG. 2 is a flow chart of the steps of one input method embodiment of the present invention;

FIG. 3 is a block diagram of an input device according to an embodiment of the present invention;

FIG. 4 is a block diagram of an apparatus 800 for input of the present invention; and

fig. 5 is a schematic diagram of a server in some embodiments of the invention.

Detailed Description

The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, not all, embodiments of the present invention. All other embodiments, which can be obtained by a person skilled in the art without inventive step based on the embodiments of the present invention, are within the scope of protection of the present invention.

Compared with the traditional word bank which records the mapping relation between the entries and the word frequency, the embodiment of the invention provides the concept of the environmental word bank. Specifically, in the embodiment of the present invention, the mapping relationship between the entries, the historical input environment characteristics, and the word frequency may be stored in the first environment thesaurus, or a second environment thesaurus corresponding to a certain historical input environment characteristic may be constructed, and the mapping relationship between the entries and the word frequency may be stored in the second environment thesaurus. And obtaining the word frequency of the candidate item under the historical input environment characteristics through the first environment lexicon or the second environment lexicon.

The embodiment of the invention provides an input scheme, which can determine the weight corresponding to the word frequency of a candidate item corresponding to an input string of a user under the historical input environmental characteristics according to the matching degree between the current input environmental characteristics and the historical input environmental characteristics corresponding to the input string of the user, and carry out weighting processing on the word frequency of the candidate item under at least one historical input environmental characteristic according to the weight so as to obtain the target word frequency corresponding to the candidate item; and then sorting and displaying the candidate items according to the target word frequency corresponding to the candidate items.

The embodiment of the invention performs weighting processing on the word frequency of the candidate item under a certain historical input environmental characteristic, wherein the weight used by the word frequency of the candidate item under the certain historical input environmental characteristic in the weighting processing process can reflect the importance degree of the word frequency of the candidate item under the certain historical input environmental characteristic, and the weight can be obtained according to the matching degree between the current input environmental characteristic and the historical input environmental characteristic, so that the matching degree or the proximity between the word frequency of the candidate item under the certain historical input environmental characteristic and the input intention corresponding to the current input environmental characteristic can be reflected through the size of the weight.

The embodiment of the present invention may be applied to an input method program of an input mode such as keyboard symbol input, handwriting input, voice input, etc., and for convenience of description, the embodiment of the present invention refers to a code character string input by a user in the input mode as an input string. In the field of input methods, for input method programs in, for example, chinese, japanese, korean, or other languages, an input string input by a user may be generally converted into a candidate for a corresponding language. The input process of the embodiment of the invention is mainly explained by taking Chinese as an example, and other languages can be referred to each other. It is to be understood that the chinese input method may include, but is not limited to, a full pinyin, a simple pinyin, a stroke, a five-stroke, and the like, and the embodiment of the present invention is not limited to a specific input method program corresponding to a certain language.

The input method program may be run on a terminal, and the terminal specifically includes, but is not limited to: smart phones, tablet computers, e-book readers, MP3 (moving Picture Experts Group Audio Layer III) players, MP4 (moving Picture Experts Group Audio Layer IV) players, laptop portable computers, car-mounted computers, desktop computers, set-top boxes, smart televisions, wearable devices, and the like.

According to some embodiments, the input string may include, but is not limited to: a key symbol or a combination of a plurality of key symbols input by a user through a key. The key symbol may specifically include: pinyin, strokes, kana, etc.

Method embodiment one

Referring to fig. 1, a flowchart illustrating steps of an embodiment of a method for processing a thesaurus according to the present invention is shown, and specifically may include:

step 101, collecting historical input behavior data of a user; the historical input behavior data may include: the method comprises the steps of displaying screen content and corresponding historical input environment characteristics;

and 102, establishing and storing a mapping relation among the entries, the historical input environment characteristics and the word frequency according to the historical input behavior data.

In the embodiment of the invention, the input environment characteristics can be used for representing the environment information of the terminal when the user inputs the information. The input environment characteristics can reflect the input intention of the user to a certain extent, so that the relation is established between the input environment characteristics and the input intention of the user, the input intention of the user can be indirectly identified, and the input efficiency of the user is improved.

In practical applications, the input environment features may include various types of features. Optionally, the input environment feature may include: at least one of a temporal environment feature, a location environment feature, a climate environment feature, an application environment feature, and a page environment feature.

Even if the same terminal is in the environment information which is likely to change, the time environment characteristic is a typical example. Therefore, the input environment characteristics of the embodiment of the invention can have real-time performance, and the input environment characteristics corresponding to the input string can be acquired in real time in the input process.

For an input string, its reception time may be taken as a corresponding temporal environment characteristic.

Location information obtained according to an IP (Internet Protocol) address thereof, a GPS (Global Positioning System) of the terminal, or a mobile communication network may be used as a corresponding location environment characteristic.

The corresponding application program environment characteristic can be determined by acquiring the identification characteristic of the current object which is being served by the input method program, for example, when the input method program is in operation, the GetModuleFilename is called to find the program path name 'C: \ ProgamFiles \ Microsoft OFFICE \ OFFICE11\ WINWORD. EXE', that is, the corresponding application environment characteristic is 'WinWord. Exe', that is, the input string is input in the word application program.

The page environment features may be used to characterize the page environment provided by the application or website, and optionally, the page environment may include, but is not limited to: an Instant Messaging (IM) page environment, a document page environment, a mail page environment, a password entry page environment, a game page environment, a search page environment, a travel page environment, a shopping page environment, a social page environment, a movie page environment, a reading page environment, and the like.

Of course, the input environment features of the embodiments of the present invention may include other environment features, such as physical environment features of barometric pressure, altitude, temperature, humidity, etc., in addition to the time environment feature, the location environment feature, the application environment feature, and the page environment feature. Wherein, it is understood that the embodiment of the present invention does not impose limitations on specific input environment features.

Referring to table 1, an illustration of a mapping relationship between input environment categories and input environment features according to an embodiment of the present invention is shown, where a person skilled in the art may classify input environments into corresponding input environment categories according to actual application requirements, and it can be understood that the embodiment of the present invention does not limit specific input environment categories and corresponding input environments.

TABLE 1

In practical applications, historical input behavior data of the user may be collected through the client, wherein the user may be identified through device information of the user account and/or the terminal. For example, the device information may include: IMEI (International Mobile Equipment Identity), etc. The embodiment of the invention can establish and store the mapping relation among the entries, the historical input environmental characteristics and the word frequency aiming at the historical input behavior data of a user, and provide services for the user in the input process through the mapping relation.

In embodiments of the present invention, the on-screen content may be used to represent one or more characters corresponding to an input string. The content of the screen can be characters of languages such as Chinese characters, english characters, japanese characters and the like, and the content of the screen can also be symbol combinations in the forms of characters, emoji (pictograph), pictures and the like. The color text includes but is not limited to a drawing composed of lines, symbols and words, for example, examples of the color text may include: ": p ",": o ",": etc.

The embodiment of the invention can store the content on the screen as entries. Meanwhile, historical input environment characteristics and word frequency corresponding to the entries can be stored. Optionally, the word frequency may be obtained according to the number of times of screen entry of the entry, and the word frequency may be consistent with the number of times of screen entry of the entry.

According to an embodiment, the mapping relationship among the entries, the historical input environment characteristics and the word frequency can be stored through the first environment lexicon. Referring to table 2, an illustration of a first environment thesaurus according to an embodiment of the present invention is shown, where the historical input environment characteristic may be environment information where a terminal is located when a user inputs a vocabulary entry.

TABLE 2

It is understood that, for example, the first environment thesaurus shown in table 2 is only an alternative embodiment of the thesaurus according to the embodiment of the present invention, and in fact, those skilled in the art may save the mapping relationship between the entries, the historical input environment characteristics, and the word frequency through other forms of environment thesaurus according to the actual application requirements. For example, according to another embodiment, a second environment lexicon corresponding to some historical input environment feature may be further constructed, and the mapping relationship between the terms and the word frequencies is stored through the second environment lexicon. And obtaining the word frequency of the candidate item under the historical input environment characteristics through the first environment lexicon or the second environment lexicon.

In summary, the embodiment of the present invention records the historical input behavior data of the user with the historical input environment characteristics as granularity, so that the thesaurus can have the input environment attribute, and thus the thesaurus can better and accurately meet the input requirement of the user.

Method embodiment two

Referring to fig. 2, a flowchart illustrating steps of an embodiment of an input method according to the present invention is shown, which may specifically include:

step 201, determining a weight corresponding to a word frequency of a candidate item corresponding to an input string of a user under a historical input environment characteristic according to a matching degree between a current input environment characteristic and the historical input environment characteristic corresponding to the input string of the user; the word frequency of the candidate under the characteristics of the historical input environment may be obtained according to historical input behavior data of the user, where the historical input behavior data may include: the method comprises the steps of (1) displaying contents and corresponding historical input environment characteristics;

step 202, according to the weight, carrying out weighting processing on the word frequency of the candidate item under at least one historical input environment characteristic to obtain a target word frequency corresponding to the candidate item;

and 203, sorting and displaying the candidate items according to the target word frequency corresponding to the candidate items.

In practical application, an input string of a user in an input process can be acquired, wherein the user can input the input string in input modes such as keyboard symbol input, handwriting input, voice input and the like. The embodiment of the invention mainly takes the pinyin string as an example for explanation, and the input strings corresponding to other input modes can be referred to each other.

In practical application, the candidate item corresponding to the input string of the user can be obtained by searching in the word bank according to the input string of the user. Optionally, the word stock may include: the local word stock and/or the cloud word stock, whether the local word stock or the cloud word stock, may include: the system lexicon, the user lexicon, the cell lexicon, the N-element lexicon, the environmental lexicon (including the first environmental lexicon and/or the second environmental lexicon), and the like, it can be understood that the embodiment of the present invention does not limit the specific lexicon corresponding to the candidate item search.

According to the embodiment of the invention, the weight corresponding to the word frequency of the candidate item under the historical input environment characteristic can be determined according to the matching degree between the current input environment characteristic and the historical input environment characteristic, namely the importance degree of the word frequency of the candidate item under the historical input environment characteristic.

In practical applications, the matching degree between the current input environmental characteristics and the historical input environmental characteristics may include: similarity and/or correlation, etc. The matching degree may be characterized by a specific numerical value, or may be characterized by a matching degree grade. For example, the matching degree may correspond to a value in the range of [0,1], the number of matching degree levels may be N, where N is a natural number, for example, the value of N may be 3, and the matching degree levels may include: high level, medium level and low level, of course, the embodiment of the present invention does not limit the specific matching degree level and the specific representation manner corresponding to the matching degree.

Wherein the similarity between the current input environmental characteristics and the historical input environmental characteristics can be determined by comparing the two. For example, the names of the two may be compared, or the input environment categories to which the two belong may be compared, etc., to obtain the corresponding similarity.

The degree of correlation between the current input environmental characteristics and the historical input environmental characteristics can be used to represent the degree of association between the two. In practical application, the degree of correlation between the two may be preset, or the degree of correlation between the two may be determined according to the historical input behavior data corresponding to the two. It is to be understood that the embodiment of the present invention does not limit the specific determination manner of the correlation between the current input environment characteristic and the historical input environment characteristic.

For example, the degree of correlation between any two input environment characteristics may be preset and stored in a relationship table, so that the degree of correlation between the current input environment characteristic and the historical input environment characteristic may be determined by querying the relationship table.

The process of determining the correlation between the two historical input behavior data according to the two corresponding historical input behavior data may include: and determining the correlation between the current input environmental characteristics and the historical input environmental characteristics according to the historical input behavior data of the user under the current input environmental characteristics and the historical input environmental characteristics. In practical applications, historical input behavior data of the user under the current input environmental characteristics and the historical input environmental characteristics respectively may be counted to obtain a correlation between the current input environmental characteristics and the historical input environmental characteristics, where the user involved in the historical input behavior data of the user under the current input environmental characteristics and the historical input environmental characteristics respectively may be all or part of users in the whole network. Alternatively, the co-occurrence frequency of the upper screen content under the current input environment characteristic and the historical input environment characteristic can be firstly obtained statistically, and then the correlation degree between the current input environment characteristic and the historical input environment characteristic can be obtained according to the co-occurrence frequency. The co-occurrence frequency acquisition process may include: and determining the number N of the on-screen contents under the current input environment characteristic and the historical input environment characteristic and the number M of the on-screen contents which commonly appear under the current input environment characteristic and the historical input environment characteristic, and taking the M/N as the co-occurrence frequency. In practical applications, the co-occurrence frequency may be directly used as the correlation between the two, or the co-occurrence frequency may be further processed to obtain the correlation between the two, for example, the co-occurrence frequency may be adjusted according to the feedback information of the user to obtain the correlation between the two. Specifically, the feedback information may include: the positive feedback and the negative feedback may be performed by increasing the co-occurrence frequency according to the positive feedback information, or may be performed by decreasing the co-occurrence frequency according to the negative feedback information, and so on.

In an alternative embodiment of the present invention, the weight may be proportional to the matching degree, that is, the higher the matching degree is, the greater the weight is.

In another optional embodiment of the present invention, a mapping relationship table between the matching degree and the weight may be preset and stored, so that step 201 may determine the weight corresponding to the word frequency of the candidate item corresponding to the input string of the user under the characteristics of the historical input environment by querying the mapping relationship table.

Referring to table 3, an example of a mapping relationship table according to an embodiment of the present invention is shown, which may specifically include: matching degree and corresponding weight W, wherein the matching degree may include: the matching degree grades of high grade, middle grade, low grade, etc. the weight W can be gradually reduced according to the order from high grade to low grade.

TABLE 3

Degree of matching	Weight W
		Advanced	2
Middle-grade	1
		Low grade	0.5

In another alternative embodiment of the present invention, in addition to determining the weight according to the matching degree between the current input environmental characteristic and the historical input environmental characteristic, the weight may be determined according to other factors, and the other factors may include: the process of determining the weight corresponding to the word frequency of the candidate item corresponding to the input string of the user under the characteristic of the historical input environment correspondingly may include: and determining the weight corresponding to the word frequency of the candidate item corresponding to the input string of the user under the historical input environmental characteristics according to the matching degree between the current input environmental characteristics and the historical input environmental characteristics, the historical screen-up time of the entry corresponding to the candidate item and/or the word frequency of the candidate item under the historical input environmental characteristics.

For the candidate corresponding entry, the corresponding historical screen-up time may include: the latest historical screen-up time, that is, the time when the entry corresponding to the candidate item was last input by the user, may reflect the current importance degree of the entry corresponding to the candidate item to the user. Generally, the closer the latest historical screen-up time is to the current, the higher the importance degree of the entry corresponding to the candidate item to the user is currently, and conversely, the farther the latest historical screen-up time is from the current, the lower the importance degree of the entry corresponding to the candidate item to the user is currently.

The word frequency of the candidate under the characteristic of the historical input environment can be the input frequency or the screen-on frequency of the entry corresponding to the candidate under the characteristic of the historical input environment. The word frequency of the candidate under the characteristics of the historical input environment can reflect the importance degree of the entry corresponding to the candidate to the user. Generally, the higher the word frequency of the candidate under the history input environment characteristic is, the higher the importance degree of the entry corresponding to the candidate to the user is, and conversely, the lower the word frequency of the candidate under the history input environment characteristic is, the lower the importance degree of the entry corresponding to the candidate to the user is.

In practical application, corresponding sub-weights can be determined according to the matching degree between the current input environment characteristic and the historical input environment characteristic, the historical screen-on time of the candidate item corresponding to the entry and/or the word frequency of the candidate item under the historical input environment characteristic, and then the plurality of sub-weights are fused to obtain the weight. Specifically, a first sub-weight Wa, a second sub-weight Wb and/or a third sub-weight Wc corresponding to the matching degree between the current input environment feature and the historical input environment feature, the historical screen time of the entry corresponding to the candidate, and/or the word frequency of the candidate under the historical input environment feature may be obtained, respectively, and then the first sub-weight Wa, the second sub-weight Wb and/or the third sub-weight Wc may be weighted and averaged to obtain the weight W. In the weighted averaging process, weights corresponding to the first sub-weight Wa, the second sub-weight Wb and/or the third sub-weight Wc may be determined by those skilled in the art according to practical application requirements, and the specific weights corresponding to the first sub-weight Wa, the second sub-weight Wb and/or the third sub-weight Wc are not limited in the embodiment of the present invention.

For a person skilled in the art to better understand the embodiment of the present invention, the input method of the embodiment of the present invention is described herein by a specific example, which relates that the candidate corresponding to the input string "lyq" may include: "dress", "tourist area", and "router", etc., wherein the input intention of the user under the current input environmental characteristics may include: in the shopping environment, the input intent of the user is: inputting the one-piece dress through an input string 'lyq'; in a travel environment, the input intent of the user is: inputting 'tourism area' through an input string 'lyq'; in the search environment, the input intent of the user is: by inputting the string "lyq" input "router", etc., the input method of the embodiment of the present invention may include:

step S1, learning words for the on-screen content under the historical input environment characteristics to obtain a mapping relation among entries, the historical input environment characteristics and word frequencies, and storing the mapping relation into an environment word bank (such as the first environment word bank);

specifically, the word learning is performed on the on-screen content K under the input environment characteristic x, the input environment characteristic y and the input environment characteristic z, so that word frequencies K.x, K.y and K.z corresponding to the on-screen content K can be obtained. Wherein, the input environment feature x, the input environment feature y and the input environment feature z may be: shopping environment, tourism environment and search environment, on-screen content K may include: one-piece dress, tourist area, router, etc.

S2, when a user inputs under the current input environment characteristics, determining the weight corresponding to the word frequency of the candidate item corresponding to the input string of the user under the historical input environment characteristics according to the matching degree between the current input environment characteristics and the historical input environment characteristics corresponding to the input string of the user, and performing weighting processing on the word frequency of the candidate item under at least one historical input environment characteristic according to the weight to obtain the target word frequency corresponding to the candidate item;

wherein, the matching degree may include: for example, if the current input environment feature is the same as the input environment feature x recorded in the environment thesaurus, the matching degree between the current input environment feature and the input environment feature x may be considered as 100%, and therefore, the weight corresponding to the word frequency of the candidate under the input environment feature x may be increased. Similarly, the weights corresponding to the word frequencies under the historical input environment characteristics such as the input environment characteristic y and the input environment characteristic z recorded in the environment lexicon can be obtained according to the matching degree. It should be noted that the weight may be proportional to the matching degree, that is, the higher the matching degree is, the greater the weight is, and therefore, the corresponding weight may be the highest for the historical input environment feature that is the same as the current input environment feature and is recorded in the environment thesaurus.

As an application example, assuming that the current input environment is characterized by a shopping environment, and the word frequency of the candidate "one-piece dress" recorded in the environment thesaurus in the shopping environment, the search environment and the communication environment is 5, 3 and 2 respectively, the candidate "one-piece dress" may be: 5+3+2=10, and according to the matching degree between the current input environment features and the historical environment features recorded in the environment lexicon, the embodiment of the present invention can obtain weights corresponding to the word frequencies of the candidate item "one-piece dress" in the shopping environment, the search environment and the communication environment respectively: 2. 1 and 0.5, and further obtaining a target word frequency corresponding to a candidate item 'one-piece dress': (2*5) + (1*3) + (0.5 × 2) =14, and 14>, the position of the candidate "one-piece dress" in the sorting result of the candidates can be determined, and the input efficiency of the user can be improved.

As an application example, assuming that the current input environment characteristic is a travel environment, and the word frequencies of the candidate item "travel zone" recorded in the environment thesaurus in the travel environment, the search environment and the communication environment are 5, 3 and 2, respectively, according to the conventional processing logic, the candidate item "travel zone" may be: 5+3+2=10, and according to the matching degree between the current input environment characteristics and the historical environment characteristics recorded in the environment lexicon, the embodiment of the invention can obtain weights corresponding to the word frequencies of the candidate item "tourist area" in the tourist environment, the search environment and the communication environment respectively: 2. 1 and 0.5, and further obtaining a target word frequency corresponding to a candidate item 'tourist area': (2*5) + (1*3) + (0.5 × 2) =14, and 14>, the position of the candidate item "tourist area" in the sorting result of the candidate item can be determined, and the input efficiency of the user is improved.

To sum up, the input method of the embodiment of the present invention performs weighting processing on the word frequency of the candidate item under the history input environment characteristic, wherein the weight used for the word frequency of the candidate item under the history input environment characteristic in the weighting processing process may reflect the importance degree of the word frequency of the candidate item under the history input environment characteristic, and since the weight may be obtained according to the matching degree between the current input environment characteristic and the history input environment characteristic, the matching degree or the proximity between the word frequency of the candidate item under the history input environment characteristic and the input intention corresponding to the current input environment characteristic may be reflected by the magnitude of the weight, so that the weighting processing of the embodiment of the present invention may increase the word frequency under the history input environment characteristic closer to the input intention corresponding to the current input environment characteristic, and therefore, the candidate item is ranked according to the target word frequency obtained by the weighting processing, the ranking result of the candidate item may better conform to the input intention corresponding to the current input environment characteristic, and further may improve the input efficiency of the user.

It should be noted that, for simplicity of description, the method embodiments are described as a series of combinations of movement, but those skilled in the art should understand that the embodiments are not limited by the described sequence of movement, because some steps can be performed in other sequences or simultaneously according to the embodiments of the present invention. Further, those skilled in the art will appreciate that the embodiments described in the specification are presently preferred and that no moving act is required as an embodiment of the invention.

Device embodiment

Referring to fig. 3, a block diagram of an embodiment of an input device according to the present invention is shown, which may specifically include:

a weight determining module 301, configured to determine, according to a matching degree between a current input environment feature and a historical input environment feature corresponding to an input string of a user, a weight corresponding to a word frequency of a candidate item corresponding to the input string of the user under the historical input environment feature; the word frequency of the candidate under the characteristics of the historical input environment may be obtained according to historical input behavior data of the user, where the historical input behavior data may include: the method comprises the steps of (1) displaying contents and corresponding historical input environment characteristics;

a weighting processing module 302, configured to perform weighting processing on the word frequency of the candidate item under at least one historical input environment characteristic according to the weight, so as to obtain a target word frequency corresponding to the candidate item; and

and the ranking presentation module 303 is configured to rank and present the candidate items according to the target word frequency corresponding to the candidate items.

Optionally, the matching degree between the current input environmental feature and the historical input environmental feature may include: a degree of correlation between the current input environmental characteristic and the historical input environmental characteristic.

Optionally, the weight determining module 301 may include:

and the weight determining submodule is used for determining the weight corresponding to the word frequency of the candidate item corresponding to the input string of the user under the characteristic of the historical input environment according to the matching degree between the current input environment characteristic and the historical input environment characteristic, the historical screen-up time of the candidate item corresponding to the entry and/or the word frequency of the candidate item under the characteristic of the historical input environment.

Optionally, the current input environment feature and/or the historical input environment feature may include: at least one of a temporal environment feature, a location environment feature, a climate environment feature, an application environment feature, and a page environment feature.

Optionally, the apparatus may further include:

the collection module is used for collecting historical input behavior data of a user; the historical input behavior data may include: the method comprises the steps of displaying screen content and corresponding historical input environment characteristics;

For the device embodiment, since it is basically similar to the method embodiment, the description is simple, and for the relevant points, refer to the partial description of the method embodiment.

The embodiments in the present specification are all described in a progressive manner, and each embodiment focuses on differences from other embodiments, and portions that are the same and similar between the embodiments may be referred to each other.

With regard to the apparatus in the above-described embodiment, the specific manner in which each module performs the operation has been described in detail in the embodiment related to the method, and will not be elaborated here.

Embodiments of the present invention also provide an apparatus for input, comprising a memory, and one or more programs, wherein the one or more programs are stored in the memory and configured for execution by the one or more processors to include instructions for: determining the weight corresponding to the word frequency of the candidate item corresponding to the input string of the user under the historical input environment characteristics according to the matching degree between the current input environment characteristics and the historical input environment characteristics corresponding to the input string of the user; the word frequency of the candidate item under the historical input environment characteristics is obtained according to historical input behavior data of a user, and the historical input behavior data comprises: the method comprises the steps of (1) displaying contents and corresponding historical input environment characteristics; according to the weight, carrying out weighting processing on the word frequency of the candidate item under at least one historical input environment characteristic to obtain a target word frequency corresponding to the candidate item; and sorting and displaying the candidate items according to the target word frequency corresponding to the candidate items.

Optionally, the determining a weight corresponding to a word frequency of a candidate item corresponding to an input string of the user under the characteristics of the historical input environment includes:

Optionally, the device is also configured to execute the one or more programs by the one or more processors including instructions for:

and establishing and storing a mapping relation among the entries, the historical input environmental characteristics and the word frequency according to the historical input behavior data.

Fig. 4 is a block diagram illustrating a structure of an apparatus for input 800 as a terminal according to an exemplary embodiment. For example, the apparatus 800 may be a mobile phone, a computer, a digital broadcast terminal, a messaging device, a game console, a tablet device, a medical device, an exercise device, a personal digital assistant, and the like.

Referring to fig. 4, the apparatus 800 may include one or more of the following components: processing component 802, memory 804, power component 806, multimedia component 808, audio component 810, input/output (I/O) interface 812, sensor component 814, and communications component 816.

The processing component 802 generally controls overall operation of the device 800, such as operations associated with display, telephone calls, data communications, camera operations, and recording operations. The processing element 802 may include one or more processors 820 to execute instructions to perform all or a portion of the steps of the methods described above. Further, the processing component 802 can include one or more modules that facilitate interaction between the processing component 802 and other components. For example, the processing component 802 can include a multimedia module to facilitate interaction between the multimedia component 808 and the processing component 802.

The memory 804 is configured to store various types of data to support operation at the device 800. Examples of such data include instructions for any application or method operating on device 800, contact data, phonebook data, messages, pictures, videos, and so forth. The memory 804 may be implemented by any type or combination of volatile or non-volatile memory devices, 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 or optical disks.

Power components 806 provide power to the various components of device 800. The power components 806 may include a power management system, one or more power supplies, and other components associated with generating, managing, and distributing power for the apparatus 800.

The multimedia component 808 includes a screen that provides an output interface between the device 800 and a 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 an input signal from a 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 boundary of a 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 facing camera and/or a rear facing camera. The front-facing camera and/or the rear-facing camera may receive external multimedia data when the device 800 is in an operating mode, such as a shooting mode or a video mode. Each front camera and rear camera may be a fixed optical lens system or have a focal length and optical zoom capability.

The audio component 810 is configured to output and/or input audio signals. For example, the audio component 810 includes a Microphone (MIC) configured to receive external audio signals when the apparatus 800 is in an operational mode, such as a call mode, a recording mode, and a voice recognition mode. The received audio signal may further be stored in the memory 804 or transmitted via the communication component 816. In some embodiments, audio component 810 also includes a speaker for outputting audio signals.

The I/O interface 812 provides an interface between the processing component 802 and peripheral interface modules, which may be keyboards, click wheels, buttons, etc. These buttons may include, but are not limited to: a home button, a volume button, a start button, and a lock button.

The sensor assembly 814 includes one or more sensors for providing various aspects of state assessment for the device 800. For example, the sensor assembly 814 may detect the open/closed state of the device 800, the relative positioning of the components, such as a display and keypad of the apparatus 800, the sensor assembly 814 may also detect a change in position of the apparatus 800 or a component of the apparatus 800, the presence or absence of user contact with the apparatus 800, orientation or acceleration/deceleration of the apparatus 800, and a change in temperature of the apparatus 800. 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 a light 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 acceleration sensor, a gyroscope sensor, a magnetic sensor, a pressure sensor, or a temperature sensor.

The communication component 816 is configured to facilitate communications between the apparatus 800 and other devices in a wired or wireless manner. The device 800 may 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 broadcast signals or broadcast related information from an external broadcast management system via a broadcast channel. In an exemplary embodiment, the communication component 816 further includes a Near Field Communication (NFC) module to facilitate short-range communications. For example, the NFC module may be implemented based on Radio Frequency Identification (RFID) technology, infrared data association (IrDA) technology, ultra Wideband (UWB) technology, bluetooth (BT) technology, and other technologies.

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, micro-controllers, microprocessors or other electronic components for performing the above-described methods.

In an exemplary embodiment, a non-transitory computer-readable storage medium comprising instructions, such as the memory 804 comprising instructions, executable by the processor 820 of the device 800 to perform the above-described method is also provided. For example, the non-transitory computer readable storage medium may be a ROM, a Random Access Memory (RAM), a CD-ROM, a magnetic tape, a floppy disk, an optical data storage device, and the like.

Fig. 5 is a schematic diagram of a server in some embodiments of the invention. The server 1900 may vary widely by configuration or performance and may include one or more Central Processing Units (CPUs) 1922 (e.g., one or more processors) and memory 1932, one or more storage media 1930 (e.g., one or more mass storage devices) storing applications 1942 or data 1944. Memory 1932 and storage medium 1930 can be, among other things, transient or persistent storage. The program stored in the storage medium 1930 may include one or more modules (not shown), each of which may include a sequence of instructions operating on a server. Still further, a central processor 1922 may be provided in communication with the storage medium 1930 to execute a series of instruction operations in the storage medium 1930 on the server 1900.

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-output interfaces 1958, one or more keyboards 1956, and/or one or more operating systems 1941, such as Windows Server, mac OS XTM, unixTM, linuxTM, freeBSDTM, etc.

A non-transitory computer readable storage medium in which instructions, when executed by a processor of an apparatus (terminal or server), enable the apparatus to perform an input method, the method comprising: determining the weight corresponding to the word frequency of the candidate item corresponding to the input string of the user under the historical input environmental characteristics according to the matching degree between the current input environmental characteristics and the historical input environmental characteristics corresponding to the input string of the user; the word frequency of the candidate item under the historical input environment characteristics is obtained according to historical input behavior data of a user, and the historical input behavior data comprises: the method comprises the steps of (1) displaying contents and corresponding historical input environment characteristics; according to the weight, carrying out weighting processing on the word frequency of the candidate item under at least one historical input environment characteristic to obtain a target word frequency corresponding to the candidate item; and sorting and displaying the candidate items according to the target word frequency corresponding to the candidate items.

Other embodiments of the invention will be apparent to those skilled in the art from consideration of the specification and practice of the invention disclosed herein. The invention is intended to cover any variations, uses, or adaptations of the invention following, in general, the principles of the invention and including such departures from the present disclosure as come within known or customary practice within the art to which the invention pertains. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the invention being indicated by the following claims.

It will be understood that the invention is not limited to the precise arrangements described above and shown in the drawings and that various modifications and changes may be made without departing from the scope thereof. The scope of the invention is limited only by the appended claims.

The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents, improvements and the like that fall within the spirit and principle of the present invention are intended to be included therein.

The present invention provides an input method, an input device and a device for inputting, and a machine-readable medium, which are described in detail above, and the principles and embodiments of the present invention are explained herein by using specific examples, and the descriptions of the above examples are only used to help understand the method and the core ideas of the present invention; meanwhile, for a person skilled in the art, according to the idea of the present invention, there may be variations in the specific embodiments and the application scope, and in summary, the content of the present specification should not be construed as a limitation to the present invention.

Claims

1. An input method, characterized in that the method comprises:

determining the weight corresponding to the word frequency of the candidate item corresponding to the input string of the user under the historical input environmental characteristics according to the matching degree between the current input environmental characteristics and the historical input environmental characteristics corresponding to the input string of the user; the word frequency of the candidate item under the historical input environment characteristics is obtained according to historical input behavior data of a current user, and the historical input behavior data comprises: the method comprises the steps of displaying screen content and corresponding historical input environment characteristics;

according to the weight, carrying out weighting processing on the word frequency of the candidate item under at least two historical input environment characteristics to obtain a target word frequency corresponding to the candidate item;

sorting the candidate items according to the target word frequency corresponding to the candidate items;

wherein the current input environment features and/or historical input environment features comprise: an application environment characteristic; the matching degree comprises: a degree of correlation between the current input environmental characteristics and the historical input environmental characteristics; and the correlation is obtained according to the co-occurrence frequency of the screen contents under the current input environment characteristics and the historical input environment characteristics.

2. The method of claim 1, wherein the determining the weight corresponding to the word frequency of the candidate item corresponding to the input string of the user under the characteristics of the historical input environment comprises:

3. The method of any one of claims 1-2, wherein the current input environmental characteristics and/or historical input environmental characteristics further comprise: at least one of a temporal environment feature, a location environment feature, a climate environment feature, and a page environment feature.

4. The method according to any one of claims 1 to 2, further comprising:

5. An input device, the device comprising:

the weight determining module is used for determining the weight corresponding to the word frequency of the candidate item corresponding to the input string of the user under the historical input environment characteristics according to the matching degree between the current input environment characteristics and the historical input environment characteristics corresponding to the input string of the user; the word frequency of the candidate item under the historical input environment characteristics is obtained according to historical input behavior data of a current user, and the historical input behavior data comprises: the method comprises the steps of displaying screen content and corresponding historical input environment characteristics;

the weighting processing module is used for carrying out weighting processing on the word frequencies of the candidate items under at least two historical input environment characteristics according to the weights so as to obtain target word frequencies corresponding to the candidate items; and

the sorting and displaying module is used for sorting and displaying the candidate items according to the target word frequency corresponding to the candidate items;

wherein the current input environment features and/or historical input environment features comprise: an application environment characteristic; the matching degree comprises: a degree of correlation between the current input environmental characteristics and the historical input environmental characteristics; and the correlation is obtained according to the co-occurrence frequency of the content on the screen under the current input environment characteristic and the historical input environment characteristic.

6. The apparatus of claim 5, wherein the weight determination module comprises:

7. The apparatus of any one of claims 5 to 6, wherein the current input environmental characteristics and/or historical input environmental characteristics further comprise: at least one of a temporal environment feature, a location environment feature, a climate environment feature, and a page environment feature.

8. The apparatus of any of claims 5 to 6, further comprising:

the collection module is used for collecting historical input behavior data of a user; the historical input behavior data comprises: the method comprises the steps of (1) displaying contents and corresponding historical input environment characteristics;

9. An apparatus for input, comprising a memory, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, the one or more programs comprising instructions for:

determining the weight corresponding to the word frequency of the candidate item corresponding to the input string of the user under the historical input environment characteristics according to the matching degree between the current input environment characteristics and the historical input environment characteristics corresponding to the input string of the user; the word frequency of the candidate under the characteristic of the historical input environment is obtained according to historical input behavior data of a current user, and the historical input behavior data comprises the following steps: the method comprises the steps of displaying screen content and corresponding historical input environment characteristics;

sorting and displaying the candidate items according to the target word frequency corresponding to the candidate items;

10. The apparatus of claim 9, wherein the determining the weight corresponding to the word frequency of the candidate corresponding to the input string of the user under the characteristics of the historical input environment comprises:

11. The apparatus of any of claims 9 to 10, wherein the current input environmental characteristics and/or historical input environmental characteristics further comprise: at least one of a temporal environment feature, a location environment feature, a climate environment feature, and a page environment feature.

12. The apparatus of any of claims 9-10, wherein the apparatus is also configured to execute the one or more programs by one or more processors includes instructions for:

13. One or more machine-readable media having instructions stored thereon that, when executed by one or more processors, cause an apparatus to perform the input method of one or more of claims 1-4.