CN111381685A

CN111381685A - Sentence association method and device

Info

Publication number: CN111381685A
Application number: CN201811639917.0A
Authority: CN
Inventors: 姚波怀; 张扬
Original assignee: Beijing Sogou Technology Development Co Ltd
Current assignee: Beijing Sogou Technology Development Co Ltd
Priority date: 2018-12-29
Filing date: 2018-12-29
Publication date: 2020-07-07
Anticipated expiration: 2038-12-29
Also published as: CN111381685B

Abstract

The embodiment of the application discloses a sentence association method and a related device, the displayed upper content can be used as a keyword to carry out network search to obtain a corresponding search result, as the corpus related to the upper content on the network is far more than a model word stock of a local high-frequency sentence model, the lower sentences corresponding to the upper content can be determined more possibly according to the search result, and the sentence association candidate items corresponding to the upper content are generated according to the determined lower sentences, so that the sentence association method and the related device not only play a role in providing input convenience for users, but also realize a sentence association function through a search mode, and improve the application range of the sentence association function.

Description

Sentence association method and device

Technical Field

The present application relates to the field of input methods, and in particular, to a sentence association method and apparatus.

Background

The input method system can associate the context candidate items based on the content of the user screen during the input process of the user, so that the user can directly screen by selecting the candidate items, and convenience is provided for the input of the user. The input method system can take the associated following sentences as sentence association candidate items through a sentence association function, the sentence association candidate items comprise sentences, and the sentences can be phrases or long sentences formed by a plurality of words. If the user selects one sentence association candidate item, more contents can be displayed on the screen at one time, and the input efficiency is improved.

At present, the function of sentence association is mainly realized by adopting an N-Gram model commonly used in large-vocabulary continuous speech recognition. The input method system trains the model by counting high-frequency sentence combinations in the historical corpus of the user, for example, if a user frequently inputs a sentence combination of 'eating grape and not spitting grape skin and not eating grape and inversely spitting grape skin' before, when the user inputs 'eating grape and not spitting grape skin' again, the input method system can associate to obtain a sentence association candidate item of 'not eating grape and inversely spitting grape skin' through model matching.

However, the current model training is based on user history corpus, and the requirement for storing occupied by an offline model lexicon is strict, so that at present, only high-frequency sentences can be extracted from the displayed upper content to train a high-frequency sentence model, and the sentence association function is realized by using the high-frequency sentence model to determine whether the current upper content has sentence association candidates of the lower sentences, so that the application range of the sentence association function is not large.

Disclosure of Invention

In order to solve the technical problem, the present application provides a sentence association method and apparatus, which not only provide convenience for the user to input, but also implement a sentence association function in a search mode, and improve the application range of the sentence association function.

The embodiment of the application discloses the following technical scheme:

in a first aspect, an embodiment of the present application provides a sentence association method, where the method includes:

acquiring the content which is displayed on the screen;

searching by taking the above content as a keyword to obtain a search result;

determining a following sentence corresponding to the above content according to the search result;

and generating sentence association candidates corresponding to the above content according to the below sentences.

Optionally, the determining, according to the search result, a following sentence corresponding to the above content includes:

dividing the search result into a plurality of divided results according to separators in the search result;

determining a first matching relation between the segmentation result and the above content, wherein the first matching relation is used for identifying the probability of the segmentation result appearing behind the above content;

and determining the segmentation result of which the first matching relation meets a first preset condition as a following sentence corresponding to the above content.

judging whether the type of the above content is a question type;

if yes, acquiring abstract content of the search result according to the content;

and taking the abstract content as a following sentence corresponding to the above content.

determining text content with similarity to the above content meeting a second preset condition from the search result;

and taking the following sentence of the text content in the search result as the following sentence corresponding to the text content.

Optionally, if a plurality of following sentences corresponding to the above-mentioned content are determined according to the search result, the generating of sentence association candidates corresponding to the above-mentioned content according to the following sentences includes:

determining ranking values respectively corresponding to the plurality of following sentences;

generating sentence association candidate items corresponding to the upper contents according to the lower sentences of which the ranking values meet the threshold;

the ranking values respectively corresponding to the following sentences are determined according to any one or combination of the following determination modes:

the first determination method comprises the following steps:

determining a second matching relationship between the plurality of following sentences and the above content respectively, wherein the second matching relationship is used for identifying the probability of the following sentences appearing after the above content;

determining ordering values respectively corresponding to the plurality of following sentences according to the second matching relation;

the second determination mode is as follows:

and determining the ranking values corresponding to the plurality of the following sentences according to the association degrees of the search results of the plurality of the following sentences and the upper content.

Optionally, the searching the content as the keyword to obtain the search result includes:

and searching in search resources related to the types of the above contents by taking the above contents as key words to obtain the search result.

Optionally, before the searching using the above content as the keyword to obtain the search result, the method further includes:

judging whether the type of the content is a preset type or belongs to a preset field;

and if so, executing the step of searching by taking the content as the keyword to obtain a search result.

Optionally, if the display object of the sentence association candidate item is a first user, the content is displayed on a screen of the first user, or the content is displayed on a screen of a second user.

In a second aspect, an embodiment of the present application provides a sentence association apparatus, where the apparatus includes an obtaining unit, a searching unit, a determining unit, and a generating unit:

the acquisition unit is used for acquiring the displayed content;

the search unit is used for searching the content as a keyword to obtain a search result;

the determining unit is used for determining a following sentence corresponding to the preceding content according to the search result;

the generating unit is used for generating sentence association candidates corresponding to the upper content according to the lower sentence.

Optionally, the determining unit is specifically configured to:

judging whether the type of the above content is a question type;

Optionally, the determining unit is specifically configured to:

Optionally, if a plurality of following sentences corresponding to the above contents are determined according to the search result, the generating unit is specifically configured to:

the first determination method comprises the following steps:

the second determination mode is as follows:

Optionally, the search unit is specifically configured to:

Optionally, the apparatus further includes a determining unit:

the judging unit is used for judging whether the type of the content is a preset type or belongs to a preset field;

and if the judging unit judges that the type of the content is a preset type or belongs to a preset field, triggering the searching unit to execute the step of searching by taking the content as a keyword to obtain a searching result.

Optionally, if the display object of the sentence association candidate item is a first user, the content is displayed on a screen of the first user, and/or the content is displayed on a screen of a second user.

In a third aspect, an embodiment of the present application provides an apparatus for sentence association, comprising a memory, and one or more programs, wherein the one or more programs are stored in the memory, and the one or more programs configured to be executed by the one or more processors include instructions for:

acquiring the content which is displayed on the screen;

searching by taking the above content as a keyword to obtain a search result;

In a fourth aspect, embodiments of the present application provide a machine-readable medium having stored thereon instructions, which, when executed by one or more processors, cause an apparatus to perform a sentence association method as described in one or more of the first aspects.

According to the technical scheme, the displayed upper content can be used as a keyword to perform network search to obtain a corresponding search result, the corpus related to the upper content on the network is far more than the model word stock of the local high-frequency sentence model, so that the lower sentence corresponding to the upper content can be determined more possibly according to the search result, and the sentence association candidate item corresponding to the upper content is generated according to the determined lower sentence.

Drawings

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

Fig. 1 is an exemplary diagram of an application scenario of a sentence association method according to an embodiment of the present application;

fig. 2 is a flowchart of a sentence association method according to an embodiment of the present application;

fig. 3 is a structural diagram of a sentence association apparatus according to an embodiment of the present application;

fig. 4 is a block diagram of an apparatus for sentence association provided in an embodiment of the present application;

fig. 5 is a block diagram of a server according to an embodiment of the present application.

Detailed Description

Embodiments of the present application are described below with reference to the accompanying drawings.

At present, the model used for determining sentence association candidates is based on a high-frequency sentence model obtained by training high-frequency sentence combinations in user historical corpus, so that at present, only often input sentence combinations can be targeted, sentence association candidates of a following sentence corresponding to the upper content are determined, once the upper content does not appear in the high-frequency sentence combinations, it is difficult to determine the sentence association candidates of the following sentence corresponding to the upper content by using the high-frequency sentence model, and the application range of the sentence association function is not large.

In order to solve the above problem, embodiments of the present application provide a sentence association method, which does not rely on a model lexicon of a local high-frequency sentence model, but the web search is carried out by taking the content on the screen as a keyword to obtain a corresponding search result, because the requirement of occupying storage on the network is far less strict than the requirement of occupying storage by a local model word stock, the linguistic data related to the above content on the network is far more than the model word stock of the local high-frequency sentence model, not only the corpus corresponding to the high-frequency sentence combination, it is more likely to determine the following sentences corresponding to various kinds of the above contents (e.g., the above contents in the high-frequency sentence combination and the above contents in the non-high-frequency sentence combination) according to the search result, and then, sentence association candidate items corresponding to the above contents are generated according to the determined following sentences, so that the application range of the sentence association function is expanded.

Next, an application scenario of the embodiment of the present application will be described with reference to the drawings. Referring to fig. 1, the application scenario may include a terminal device 101, and the terminal device 101 executes the sentence association method provided in the embodiment of the present application. The terminal device 101 may be a smart phone, a computer, a Personal Digital Assistant (PDA), a tablet computer, or the like.

Of course, in some cases, in addition to the terminal device 101, a server may be included in the application scenario, and the server may obtain the content from the terminal device 101 that has been already displayed on the screen, so that the server determines the sentence association candidate and displays the sentence association candidate on the terminal device 101. The server may be an independent server or a cluster server.

For convenience of description, the description will be made with the terminal apparatus 101 executing the sentence association method provided in the embodiment of the present application.

The terminal device 101 may obtain the content already displayed on the screen in one input interface, where the content may be content to be determined that the content may be displayed on the screen continuously. The above content is the content that is last displayed on the screen in the input interface, and the embodiment of the present application does not limit possible compositions of the above content, and may be a sentence, or a word or a phrase, for example. The input interface may refer to an interface on the terminal device for inputting and displaying the contents of the screen and the following sentences.

It should be noted that the screen-up manner of the above contents in this embodiment may include multiple manners. The following description will be given by taking a conventional screen-up mode as an example.

The first way of going up the screen may be that the user using the terminal device 101 goes up the screen.

In the present screen mode, the input interface may be any possible input interface, for example, a local document, or a conversation window for interacting with other users.

For example, a scene in which the user may continue to input content is determined for the user input content using the terminal apparatus 101. If the user using the terminal device 101 is the first user, the first user wants to input a lyric "beside the pavilion, beside the ancient road, and on the sky in succession" to express a mood, the first user first displays the content that the first user may continue to input through the input method "beside the pavilion, beside the ancient road", and then wants to display the content that the first user may continue to input to the first user, so that the first user can select "on the sky in succession" from the content and directly display the content, thereby providing convenience for the first user to input. At this time, the above content is on screen by the first user.

The second screen-up mode may be a mode in which a user interacting with the user using the terminal device 101 is on the screen in an interactive scene.

For example, the first user chats with the second user, the content on screen of the session-related user is included in the input interface, and the content that the user using the terminal device 101 may continue to input is determined for the content on screen last time. If the user using the terminal device 101 is the first user and the second user wants to ask the first user "who is zhou jeron", then the second user inputs "who is zhou jeron? "and displayed on the terminal device 101. The first user is on the pair "who is jegeren? When answering, after the first user starts the input method, the terminal device 101 may present the first user with contents that the first user may continue to input, so that the first user may select the content related to the jieren from the contents, such as "jieren is taiwan popular boy singer and musician" and directly go on the screen, which provides convenience for the first user to input. At this time, the above contents are on-screen by the second user.

A third way of being on-screen may be by a user using terminal device 101 and by a user interacting with the user using terminal device 101.

For example, the first user chats with the second user, the content on screen of the session-related user is included in the input interface, and the content that the user using the terminal device 101 may continue to input is determined for the content on screen last time. If the user using the terminal device 101 is the first user who says "i like Zhou Ji Lun very much", and the second user asks the first user who is "he is", then "i like Zhou Ji Lun very much" that the first user input and "who is? "on screen on terminal device 101. The first user is on the pair "who is he? When answering, after the first user starts the input method, the terminal device 101 may present the first user with contents that the first user may continue to input, so that the first user may select the content related to the jieren from the contents, such as "jieren is taiwan popular boy singer and musician" and directly go on the screen, which provides convenience for the first user to input. Because "who is he? "does not have complete semantics, just based on" who is he? "it is difficult to obtain the search result by searching, so it is also necessary to determine that the content with complete semantics is actually" who is mongalon "in combination with" i like mongalon well? "to search. At this time, the above contents are on-screen by the first user and the second user.

The terminal device 101 searches the content as a keyword to obtain a search result, where the search result refers to a corpus related to the content, which is acquired by the terminal device 101 from the network 102. Since the corpus of the network 102 related to the above content is much larger than the model lexicon of the local high-frequency sentence model, the following sentence corresponding to the above content can be determined according to the search result, and the following sentence refers to the sentence which appears after the above content and is adjacent to the above content.

The terminal device 101 may generate a sentence association candidate corresponding to the above-mentioned content according to the below-mentioned sentence, where the sentence association candidate may be a content that is determined to be likely to be displayed continuously after the above-mentioned content. In this way, the terminal device 101 may display the sentence association candidates to the user using the terminal device 101, and the user using the terminal device 101 may directly screen a following sentence corresponding to the above-mentioned content by selecting the sentence association candidates, thereby providing convenience for the user input.

Next, a sentence association method provided by an embodiment of the present application will be described with reference to the drawings. Referring to fig. 2, the method includes:

s201, acquiring the displayed contents.

In this embodiment, a user using a terminal device is described as a first user. Under different application scenes, conditions for triggering the terminal device to acquire the content are different.

For example, in the first screen-up mode described above, after the first user finishes the screen-up of the content, the terminal device may be triggered to acquire the content.

For another example, in the second and third screen-up modes described above, when the first user clicks the input box to invoke the keyboard, the terminal device may be triggered to obtain the content.

The manner in which the terminal device determines the content may include multiple manners, and in one possible implementation, the content may be content that the terminal device intelligently determines to contain complete semantics.

S202, searching by taking the content as a keyword to obtain a search result.

Since the corpus related to the above content is much more than the model lexicon of the local high-frequency sentence model on the network, in order to ensure that the following sentence corresponding to the above content is more likely to be determined, the search result can be obtained from the network.

It should be noted that, a network may include many search resources, and among these search resources, different search resources have different degrees of correlation with the content, some search resources have a large degree of correlation with the content, and some search resources have a small degree of correlation with the content. When the degree of the correlation between the search resource and the content is larger than a certain threshold value, the search resource can be considered to be related to the content, otherwise, the search resource is not related to the content. Therefore, in a possible implementation manner, the above content can be used as a keyword, and a search is performed in a search resource related to the above content to obtain a search result. Because the search resource is related to the content of the text, the obtained search result is a search result with a higher degree of relation to the content of the text, so that the subsequently determined text and the sentence association candidate determined according to the text are also more related to the content of the text, and the sentence association candidate has a higher possibility of including the text which is continuously input by the first user, so that the first user is more likely to select the continuously input text from the sentence association candidates. In addition, because the search result is obtained only from the search resource related to the content, the search result is not required to be obtained from the search resource unrelated to the content, the number of the search results is greatly reduced, the processing burden of the terminal equipment on subsequently processing the search result is reduced, and the processing efficiency is improved.

In a possible implementation manner, the search resource related to the above content may be determined according to the type of the above content, for example, the above content is "outside the pavilion, ancient street edge", and the type of the above content is a song type, so that the degree of correlation between the search resource belonging to the song type and the above content is relatively large, and may be greater than the first threshold, and the search resource belonging to the song type may be used as the search resource related to the above content. In this way, when the above content is searched, the search result can be obtained by only searching in the search resource of the song class.

S203, determining a following sentence corresponding to the above content according to the search result.

The search result is a corpus related to the above content, and the search result may include a following sentence corresponding to the above content, so that the following sentence corresponding to the above content may be determined according to the search result.

And S204, generating sentence association candidates corresponding to the above content according to the below sentences.

The determined context sentence is a sentence which the first user may continue to input after the above content, and the sentence association candidate generated by the determined context sentence may be presented to the first user so that the first user may screen the context sentence by selecting the sentence association candidate.

It should be noted that some trigger conditions may exist in the sentence association method provided in the embodiment of the present application. In some cases, since the above content may be the above content in the high-frequency sentence combination in the history data of the first user, it may also be the above content in the non-high-frequency sentence combination. For the above content in the high-frequency sentence combination, sentence association candidates can be accurately generated by the conventional sentence association method without performing the subsequent processing procedures of S202-S204. Therefore, in order to avoid performing the subsequent processing procedures of S202-S204 on the content in the high-frequency sentence combination, reduce the triggering of S202-S204, reduce the processing load of the terminal device, and improve the generation efficiency of sentence association candidates, before performing S202, it may be determined whether the content has a corresponding context sentence by using the local high-frequency sentence model, and if so, the context sentence corresponding to the content is directly determined by using the local high-frequency sentence model, so as to reduce the processing load of the terminal device and improve the generation efficiency of sentence association candidates. If not, the step of S202 is executed to ensure that sentence association candidates can be generated for the above content that is not applicable in the conventional manner.

In other cases, since the types of the above contents may include a great variety, some types of the above contents may be suitable for determining sentence association candidates by the sentence association method provided by the embodiment of the present application, and some types of the above contents may not be suitable for determining sentence association candidates by the sentence association method provided by the embodiment of the present application. Therefore, in order to ensure that the subsequent processing procedures of S202-S204 are only performed on the content of the above that is suitable for the sentence association method, reduce unnecessary triggering of S202-S204, and reduce the processing burden of the terminal device, before performing S202, it may be first determined whether the type of the content of the above is a preset type or belongs to a preset field, and if the type of the content of the above is a preset type or belongs to a preset field, for example, the type of the content of the above belongs to a movie field, a television play field, a sports field, or the type of the content of the above is a star character class, a poetry class, a proverbial class, or the like, it is described that the content of the above is suitable for the sentence association method provided by the embodiment of the present application, the step of S202 is performed. It should be noted that, in executing S203, the manner of determining the following sentence may include various manners. Next, the following sentence will be described in a manner of determination.

In one possible implementation, the following sentence may be determined according to a matching relationship, and the matching relationship may be a probability for identifying a content appearing after the above content.

In some cases, the context content and the following sentence may constitute a fixed form of context content, such as poems, lyrics, adage, colloquialisms, etc., and it may be determined which part of the search result can be used as the following sentence according to the matching relationship between the context content and the parts of the search result.

Since the search result may include the above content, the following sentence and other content, there may be a separator between the above content, the following sentence and other content, and the separator may include punctuation, space and other symbols for separating sentences.

Dividing the search result into a plurality of parts according to the separators in the search result, wherein each part is used as a division result, and each division result can be a sentence (which can comprise phrases or long sentences) because the separators are used as the division basis; a first matching relationship between the segmented result and the above content is determined, wherein the first matching relationship is used for identifying the probability of the segmented result appearing after the above content. If the first matching relationship satisfies the first preset condition, the probability that the segmentation result appears after the above content is considered to be relatively high, and therefore, the segmentation result whose first matching relationship satisfies the first preset condition can be determined as the following sentence corresponding to the above content.

In one possible implementation, the following sentence may be determined in such a way that the following sentence is determined according to the text content similar to the above content.

In such an implementation, the above content may make it difficult to determine the following sentence by using the first matching relationship obtained by matching the above content itself with the segmentation result in the search result due to non-normative expression, excessive colloquialization, and the like. And text content with certain semantic similarity with the above content exists in the search result, and the higher the similarity is, the more likely the following sentence of the text content is to be the following sentence of the above content.

In this case, a text content whose similarity to the above content satisfies a second preset condition may be determined from the search result, where the similarity satisfies the second preset condition may be that the similarity of the text content to the above content is relatively high, and the probability that the following sentence of the text content is the following sentence of the above content is relatively high, and therefore, the following sentence of the text content in the search result may be regarded as the following sentence corresponding to the above content.

Therefore, the method can ensure that the following sentences are determined for the text contents which are expressed in an irregular and excessively spoken manner by determining the similar text contents for the text contents, further determine the corresponding sentence association candidate items, and improve the application range of the sentence association function.

In one possible implementation, the following sentence may be determined according to the summary content of the search result.

The type of the above content may be many, in some cases, the type of the above content may be a question type, and accordingly, the search result may be an answer to the above content, the search result includes a related introduction of an object mentioned in the above content, and the search result includes a large amount of information of the object, however, the following sentence is an input interface for generating a sentence association candidate so that the first user can select a satisfactory following sentence from the input interface, and in general, the following sentence is not too long, and only key information of the search result for the object needs to be included. Since the abstract content in the search result can reflect the key information of the target, if the type of the above content is determined to be the question type, the abstract content of the search result can be obtained according to the above content, and the abstract content is used as the following sentence corresponding to the above content.

For example, a second user input of "who is zhou jenlong? "and screen on the terminal device corresponding to the first user," who is a zhou jilun? "as above, Zhougelon is the object included in the above. The search result obtained by the terminal device executing S202 may include the searchleaux of zhou-jiron, which includes a lot of information, and it is difficult to use all the information of zhou-jiron in the searchleaux as a following sentence, so the summary content of the search result can be determined according to the above content, for example, "zhou-jiron is a singer of a bane popular with taiwan, and a music player".

Therefore, by determining the context sentence according to the abstract content, the determined context sentence can be more concise, and the first user is more likely to select a satisfactory context sentence from the sentence association candidates.

It should be noted that after S203 is executed, the determined following sentence may include one or more than one. Due to the size limitation of the input interface and the consideration of the efficiency of selecting sentence association candidates, the number of sentence association candidates presented to the first user by the terminal device is limited. Therefore, when a plurality of following sentences are determined, the following sentences more likely to be the first user continuation input contents can be selected therefrom as the sentence association candidates. The probability that the following sentence is used as the first user to continuously input the content can be embodied by the ranking value corresponding to the following sentence, and the greater the ranking value is, the greater the probability that the following sentence is used as the first user to continuously input the content is.

In this case, one possible implementation manner of S204 is to determine ranking values corresponding to the plurality of following sentences, and generate sentence association candidates corresponding to the above contents according to the following sentences whose ranking values satisfy the threshold value. And generating sentence association candidates according to the following sentences with larger ranking values, so that the possibility that the first user determines the following sentences by selecting the sentence association candidates can be further improved.

Wherein, the ranking values respectively corresponding to a plurality of following sentences are determined according to the following mode.

The first determination mode is to determine a second matching relationship between each of the plurality of following sentences and the upper content, the second matching relationship is used for identifying the probability that the following sentence appears behind the upper content, the higher the probability is, the more likely the following sentence is to be a sentence which is continuously input by the first user, and the ranking values corresponding to the plurality of following sentences are determined according to the second matching relationship.

In addition, since the association degree of different search results with the above content is different when the search result is obtained through S202, the greater the association degree is, the more accurate the following sentence determined according to the search result is, and the greater the possibility that the first user continues to input the following sentence is. Therefore, the second determination manner is to determine the ranking values corresponding to the plurality of following sentences according to the association degree between the search results of the plurality of following sentences and the above content.

Of course, in order to improve the accuracy of determining the ranking value, the first determination method and the second determination method may be combined to determine the ranking values corresponding to a plurality of following sentences.

Based on the corresponding embodiment of fig. 2, the present embodiment provides a sentence association apparatus, referring to fig. 3, the apparatus includes an acquisition unit 301, a search unit 302, a determination unit 303, and a generation unit 304:

the acquiring unit 301 is configured to acquire the above content that has been displayed on the screen;

the searching unit 302 is configured to search the above content as a keyword to obtain a search result;

the determining unit 303 is configured to determine a following sentence corresponding to the preceding content according to the search result;

the generating unit 304 is configured to generate sentence association candidates corresponding to the above content according to the below sentence.

Optionally, the determining unit is specifically configured to:

judging whether the type of the above content is a question type;

Optionally, the determining unit is specifically configured to:

the first determination method comprises the following steps:

the second determination mode is as follows:

Optionally, the search unit is specifically configured to:

Optionally, the apparatus further includes a determining unit:

The present embodiment also provides a device for sentence association, which may be a terminal device, and fig. 4 is a block diagram illustrating a terminal device 400 according to an exemplary embodiment. For example, the terminal device 400 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, and the like.

Referring to fig. 4, the terminal device 400 may include one or more of the following components: processing components 402, memory 404, power components 406, multimedia components 408, audio components 410, input/output (I/O) interfaces 412, sensor components 414, and communication components 416.

The processing component 402 generally controls overall operation of the terminal device 400, such as operations associated with display, telephone calls, data communications, camera operations, and recording operations. The processing element 402 may include one or more processors 420 to execute instructions to perform all or part of the steps of the methods described above. Further, the processing component 402 can include one or more modules that facilitate interaction between the processing component 402 and other components. For example, the processing component 402 can include a multimedia module to facilitate interaction between the multimedia component 408 and the processing component 402.

The memory 404 is configured to store various types of data to support operations at the terminal device 400. Examples of such data include instructions for any application or method operating on the device 400, contact data, phonebook data, messages, pictures, videos, and so forth. The memory 404 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.

The power supply component 406 provides power to the various components of the terminal device 400. The power components 406 may include a power management system, one or more power supplies, and other components associated with generating, managing, and distributing power for the apparatus 400.

The multimedia component 408 comprises a screen providing an output interface between the terminal device 400 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 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 408 includes a front facing camera and/or a rear facing camera. The front camera and/or the rear camera may receive external multimedia data when the terminal device 400 is in an operation mode, such as a photographing 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 410 is configured to output and/or input audio signals. For example, audio component 410 includes a Microphone (MIC) configured to receive external audio signals when apparatus 400 is in an operational mode, such as a call mode, a recording mode, and a voice recognition mode. The received audio signals may further be stored in the memory 404 or transmitted via the communication component 416. In some embodiments, audio component 410 also includes a speaker for outputting audio signals.

The I/O interface 412 provides an interface between the processing component 402 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 component 414 includes one or more sensors for providing various aspects of status assessment for the terminal device 400. For example, sensor component 414 can detect an open/closed status of terminal device 400, the relative positioning of components, such as a display and keypad of terminal device 400, sensor component 414 can also detect a change in the position of terminal device 400 or a component of terminal device 400, the presence or absence of user contact with terminal device 400, orientation or acceleration/deceleration of terminal device 400, and a change in the temperature of terminal device 400. The sensor assembly 414 may include a proximity sensor configured to detect the presence of a nearby object without any physical contact. The sensor assembly 414 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 414 may also include an acceleration sensor, a gyroscope sensor, a magnetic sensor, a pressure sensor, or a temperature sensor.

The communication component 416 is configured to facilitate wired or wireless communication between the terminal device 400 and other devices. The terminal device 400 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 416 receives broadcast signals or broadcast related information from an external broadcast management system via a broadcast channel. In an exemplary embodiment, the communication component 416 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 terminal device 400 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 404 comprising instructions, executable by the processor 420 of the terminal device 400 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.

A non-transitory computer readable storage medium having instructions therein which, when executed by a processor of a mobile terminal, enable the mobile terminal to perform a sentence association method, the method comprising:

acquiring the content which is displayed on the screen;

searching by taking the above content as a keyword to obtain a search result;

The device for sentence association provided in this embodiment may also be a server, and fig. 5 is a schematic structural diagram of the server in this embodiment of the present invention. The server 500 may vary widely in configuration or performance and may include one or more Central Processing Units (CPUs) 522 (e.g., one or more processors) and memory 532, one or more storage media 530 (e.g., one or more mass storage devices) storing applications 542 or data 544. Memory 532 and storage media 530 may be, among other things, transient storage or persistent storage. The program stored on the storage medium 530 may include one or more modules (not shown), each of which may include a series of instruction operations for the server. Still further, the central processor 522 may be configured to communicate with the storage medium 530, and execute a series of instruction operations in the storage medium 530 on the server 500.

The server 500 may also include one or more power supplies 526, one or more wired or wireless network interfaces 550, one or more input-output interfaces 558, one or more keyboards 556, and/or one or more operating systems 541, such as Windows Server, Mac OS XTM, UnixTM, LinuxTM, FreeBSDTM, etc.

Those of ordinary skill in the art will understand that: all or part of the steps for realizing the method embodiments can be completed by hardware related to program instructions, the program can be stored in a computer readable storage medium, and the program executes the steps comprising the method embodiments when executed; and the aforementioned storage medium may be at least one of the following media: various media that can store program codes, such as read-only memory (ROM), RAM, magnetic disk, or optical disk.

It should be noted that, in the present specification, all the embodiments are described in a progressive manner, and the same and similar parts among the embodiments may be referred to each other, and each embodiment focuses on the differences from the other embodiments. In particular, for the apparatus and system embodiments, since they are substantially similar to the method embodiments, they are described in a relatively simple manner, and reference may be made to some of the descriptions of the method embodiments for related points. The above-described embodiments of the apparatus and system are merely illustrative, and the units described as separate parts may or may not be physically separate, and the parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment. One of ordinary skill in the art can understand and implement it without inventive effort.

The above description is only one specific embodiment of the present application, but the scope of the present application is not limited thereto, and any changes or substitutions that can be easily conceived by those skilled in the art within the technical scope of the present application should be covered by the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.

Claims

1. A sentence association method, the method comprising:

acquiring the content which is displayed on the screen;

searching by taking the above content as a keyword to obtain a search result;

2. The method of claim 1, wherein the determining a following sentence corresponding to the above content according to the search result comprises:

3. The method of claim 1, wherein the determining a following sentence corresponding to the above content according to the search result comprises:

judging whether the type of the above content is a question type;

4. The method of claim 1, wherein the determining a following sentence corresponding to the above content according to the search result comprises:

5. The method according to any one of claims 1 to 4, wherein if a plurality of following sentences corresponding to the above content are determined according to the search result, the generating sentence association candidates corresponding to the above content according to the following sentences comprises:

the first determination method comprises the following steps:

the second determination mode is as follows:

6. The method of claim 1, wherein the searching the above content as the keyword to obtain the search result comprises:

7. The method of claim 1, wherein before the searching the content as the keyword to obtain the search result, the method further comprises:

8. A sentence association apparatus is characterized by comprising an acquisition unit, a search unit, a determination unit, and a generation unit:

the acquisition unit is used for acquiring the displayed content;

9. An apparatus for sentence association, comprising a memory, and one or more programs, wherein the one or more programs are stored in the memory and configured for execution by one or more processors the one or more programs include instructions for:

acquiring the content which is displayed on the screen;

searching by taking the above content as a keyword to obtain a search result;

10. A machine-readable medium having stored thereon instructions, which when executed by one or more processors, cause an apparatus to perform the sentence association method of one or more of claims 1-7.