CN110659402A

CN110659402A - Automatically providing information in an application

Info

Publication number: CN110659402A
Application number: CN201810717055.2A
Authority: CN
Inventors: 葛涛; 黄绍晗; 崔磊; 张星星; 韦福如; 周明
Original assignee: Microsoft Technology Licensing LLC
Current assignee: Microsoft Technology Licensing LLC
Priority date: 2018-06-29
Filing date: 2018-06-29
Publication date: 2020-01-07
Also published as: WO2020005654A1

Abstract

In an embodiment of the present disclosure, a scheme for automatically providing information in an application is provided. In operation, keywords may be extracted from text presented by an application. It is then determined whether the extracted keyword is of interest to the user, and expanded information associated with the keyword is generated without user intervention in response to determining that the keyword is of interest to the user, and at least a portion of the expanded information is displayed. Through the scheme, the information which the user wants to know or needs to know can be directly presented to the user, and the user does not need to search the information on the network, so that the time for the user to search can be saved, and the user experience is improved.

Description

Automatically providing information in an application

Technical Field

Embodiments of the present disclosure relate to information technology, and more particularly, to a computer-implemented method, apparatus, and computer program product for providing information.

Background

Currently, people utilize applications for presenting text to browse, edit, and obtain various information. When browsing or editing text, one may want to know detailed information about some of the content in the text. As an example of an application for presenting text, email is one of the most important ways for people to communicate with each other. People, especially employees, may spend a certain amount of time writing, viewing and replying to emails each day. It has been found that most e-mail senders request the e-mail recipient to provide certain information, such as market context information, investment interests, etc. While people can search through the internet or obtain such information in other databases, this often takes a significant amount of time. For example, in order to understand the contents of an email or reply to an email, the recipient of the email may need to collect, organize, and analyze various information on the internet in order to obtain useful information therein. This process is cumbersome and time consuming.

Disclosure of Invention

In an embodiment of the present disclosure, a scheme for automatically providing information in an application is provided. After obtaining text presented by the application, keywords may be extracted from the text and a determination may be made as to whether the extracted keywords are of interest to a user of the application. If it is determined that the user may be interested in the extracted keyword, extended information associated with the extracted keyword is generated without the user performing any action with respect to the keyword. At least a portion of the expanded information is then displayed. In this way, the information that the user wants to know or needs to know can be directly presented to the user, and the user does not need to manually search the information on the network, so that the time for the user to search can be saved, and the user experience is improved.

This summary is provided to introduce a selection of concepts in a simplified form that are further described below in the detailed description. This summary is not intended to identify key features or essential features of the claimed subject matter, nor is it intended to be used to limit the scope of the claimed subject matter.

Drawings

The above and other features, advantages and aspects of various embodiments of the present disclosure will become more apparent by referring to the following detailed description when taken in conjunction with the accompanying drawings. In the drawings, like or similar reference characters designate like or similar elements, and wherein:

FIG. 1 illustrates a block diagram of a computing device in which one or more embodiments of the present disclosure may be implemented;

FIG. 2 shows a flow diagram of a method for providing information according to an embodiment of the present disclosure;

FIG. 3 illustrates a user interface (GUI) for an email application to present received emails according to an embodiment of the present disclosure;

FIG. 4 illustrates a GUI presented by an email application in reply to the email shown in FIG. 3, according to an embodiment of the present disclosure; and

FIG. 5 illustrates a GUI presented by an email application in reply to the email shown in FIG. 3, according to an embodiment of the present disclosure.

Detailed Description

Embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. While certain embodiments of the present disclosure are shown in the drawings, it is to be understood that the present disclosure may be embodied in various forms and should not be construed as limited to the embodiments set forth herein, but rather are provided for a more thorough and complete understanding of the present disclosure. It should be understood that the drawings and embodiments of the disclosure are for illustration purposes only and are not intended to limit the scope of the disclosure.

The term "include" and variations thereof as used herein are open-ended, i.e., "including but not limited to". The term "based on" is "based, at least in part, on". The term "one embodiment" means "at least one embodiment"; the term "another embodiment" means "at least one additional embodiment"; the term "some embodiments" means "at least some embodiments". Relevant definitions for other terms will be given in the following description.

As mentioned above, when reading or editing text with an application for presenting text, a user may be interested in certain content items in the text or need to know further information of these content items. For example, if a user does not know the meaning of a term mentioned in the text, the user may need to search for the definition of the term. For another example, if a recently occurring hotspot event is mentioned in the text, the user may want to know more detailed information about the hotspot event or the progress of the hotspot event. To this end, conventionally, a user needs to manually input a word mentioned in a text to a website having a search function to obtain information associated with the word from various network resources. This manner of manually searching by the user may take a significant amount of time for the user when there are many content items in the text that are of interest to the user. If the content items relate to different areas of expertise, the user may need to search to different specialized websites, which may require frequent switching between different websites, resulting in a poor user experience.

To this end, embodiments of the present disclosure propose a scheme for automatically presenting desired information to a user. In embodiments of the present disclosure, information that may be of interest to a user is predicted for text presented by an application, and the predicted information is automatically displayed to the user without requiring the user to perform any action related to a content item in the text. The method and the device can not only save the time for obtaining the extension information by the user, but also improve the user experience when the user uses the application.

The basic principles and several exemplary embodiments of the present disclosure are explained below with reference to fig. 1 to 5. FIG. 1 illustrates a block diagram of a computing device 100 in which one or more embodiments of the present disclosure may be implemented. It should be understood that the computing device 100 shown in FIG. 1 is merely exemplary and should not be construed as limiting in any way the functionality and scope of the embodiments described in this disclosure.

As shown in FIG. 1, computing device 100 comprises device 100 in the form of a general purpose computing device. Components of computing device 100 may include, but are not limited to, one or more processors or processing units 110, memory 120, storage 130, one or more input devices 140, one or more output devices 150, and one or more communication units 160.

In some embodiments, the computing device 100 may be implemented as various user terminals or service terminals. The service terminals may be servers, mainframe computing devices, etc. provided by various service providers. A user terminal such as any type of mobile terminal, fixed terminal or portable terminal, including a mobile handset, multimedia computer, multimedia tablet, internet node, communicator, desktop computer, laptop computer, notebook computer, netbook computer, tablet computer, Personal Communication System (PCS) device, personal navigation device, Personal Digital Assistant (PDA), audio/video player, digital camera/camcorder, positioning device, television receiver, radio broadcast receiver, electronic book device, game device or any combination thereof, including accessories and peripherals of these devices or any combination thereof. It is also contemplated that computing device 100 can support any type of interface to the user (such as "wearable" circuitry, etc.).

The processing unit 110 may be a real or virtual processor and may be capable of performing various processes according to applications stored in the memory 120. In a multi-processor system, multiple processing units execute computer-executable instructions in parallel to improve the parallel processing capabilities of the apparatus 100. The processing unit 110 may also be referred to as a Central Processing Unit (CPU), microprocessor, controller, microcontroller.

Computing device 100 typically includes a number of computer storage media. Such media may be any available media that is accessible by device 100 and includes, but is not limited to, volatile and non-volatile media, removable and non-removable media. Memory 120 may be volatile memory (e.g., registers, cache, Random Access Memory (RAM)), non-volatile memory (e.g., Read Only Memory (ROM), Electrically Erasable Programmable Read Only Memory (EEPROM), flash memory), or some combination thereof.

Memory 120 may include an information providing module 125 configured to perform the functions of the various embodiments described herein. Note that in the present disclosure, the terms "information providing method" and "information providing module" are used interchangeably. The information providing module 125 may be accessed and executed by the processing unit 110 to implement the corresponding functionality.

Storage device 130 may be a removable or non-removable medium and may include a machine-readable medium, such as a flash drive, a magnetic disk, or any other medium that can be used to store information and/or data and that can be accessed within computing device 100.

The input device 140 may be one or more input devices such as a mouse, keyboard, touch screen, trackball, voice input device, and the like. Output device 150 may be one or more output devices such as a display, speakers, printer, or the like.

The communication unit 160 enables communication with another computing device over a communication medium. Additionally, the functionality of the components of the apparatus 100 may be implemented in a single computing cluster or multiple computing machines, which are capable of communicating over a communications connection. Thus, the computing device 100 may operate in a networked environment using logical connections to one or more other servers, Personal Computers (PCs), or another general network node. Computing device 100 may also communicate with one or more external devices (not shown), such as storage devices, display devices, etc., communicating with one or more devices that enable a user to interact with computing device 100, or communicating with any devices (e.g., network cards, modems, etc.) that enable computing device 100 to communicate with one or more other computing devices, as desired, via communication unit 160. Such communication may be performed via input/output (I/O) interfaces (not shown).

Computing device 100 may receive text 102 from other devices or various network resources, such as news websites, blogs, self-media, etc., by way of communication unit 160. Alternatively, the computing device 100 may also receive user-entered text 102 via the input device 140. The text 102 is passed to the information providing module 125 for processing. According to an embodiment of the present disclosure, the information providing module 125 extracts one or more keywords 104-1, 104-2, 104-3 from the text 102, determines whether the keywords are likely to be of interest to the user, and determines the expanded information 106-1, 106-2 (e.g., definitions of the keywords, introductions of the keywords, hot events associated with the keywords) to be associated with the keywords 104-1, 104-2 that are likely to be of interest to the user. Hereinafter, the keywords 104-1, 104-2, 104-3 are collectively referred to as keywords 104, and the expanded information 106-1, 106-2 are collectively referred to as expanded information 106. It should be understood that, although fig. 1 shows only 3 keywords 104 and 2 pieces of extended information 106, the number of keywords 104 and the number of extended information 106 are not limited thereto, but may be any number. The text 102 and the expanded information 106 determined by the information providing module 125 may be displayed to the user via an output device 150 (e.g., a display).

It will be appreciated that communication between the information providing module 125 and the input device 140 and the output device 150 may be accomplished by means of an interface provided by an Operating System (OS) on the computing device 100. Examples of such interfaces include, but are not limited to, various Application Programming Interfaces (APIs).

According to the information providing scheme proposed by the embodiment of the present disclosure, information that a user may want to know or need to know is predicted based on keywords in text, and the information is automatically provided to the user. Therefore, the user can obtain the content which the user may pay attention to without actively searching any related content, so that the searching time of the user is saved, and the user experience is improved.

Fig. 2 shows a flow diagram of a method 200 for providing information according to an embodiment of the present disclosure. It will be understood that the method 200 may be implemented by the computing device 100, and in particular, may be implemented by the information providing module 125 in the computing device 100. For ease and clarity in explaining the method 200 of fig. 2, reference is made to the Graphical User Interface (GUI) examples of fig. 3, 4, and 5 at the same time, where fig. 3, 4, and 5 respectively show diagrams of GUIs of processes for providing information according to embodiments of the present disclosure.

At 202, the computing device 100 extracts keywords 104 from the text 102 presented by the application. In some embodiments, the application may be any application capable of rendering content in text form, such as an email application, a document editing application, a browser, and so forth. In embodiments of the present disclosure, keywords refer to such words in the text: the word is more likely to convey the subject of the text than other words in the text, i.e., the word is more important in the text than other words. For convenience of description, the keyword extraction process is described with reference to fig. 3 by taking an email application as an example. It should be understood that embodiments of the present disclosure are not limited to email applications, but may be applied to any application capable of presenting text, such as document editing applications, browsers, and the like.

Fig. 3 shows a GUI 300 for an email application installed on computing device 100 to present received emails. The GUI 300 presents an email from MingZhou received by the user YuZheng, which contains the text 102: "I sunlight yellow read the image around Mei Tao's presentation on video analysis video capturing, an interpretation topic linking video and text". It should be understood that although english text is used as an example in the embodiments of the present disclosure, other languages such as chinese and japanese are also possible, and the embodiments of the present disclosure are not limited by the language of the text.

In some embodiments, the text 102 may be processed using some natural language processing technique to determine keywords 104 therein. Specifically, the text 102 may be first subjected to word segmentation processing to obtain words in the text 102, such as "I", "silence", "article", and the like. Then, for each of these words, various methods may be utilized to assess how important the word is to the text 102 (which may indicate the probability of the word being a keyword). The words in the text 102 are then ranked by degree of importance, such that the top ranked word or words are selected as keywords 104 for the text 102. Of course, words having a degree of importance greater than a threshold degree may also be selected as keywords 104 for the text 102.

In some embodiments, for each word in text 102, a word frequency-inverse document frequency (TF-IDF) score for the word may be calculated as a metric for evaluating the importance of the word to text 102. The basic idea of TF-IDF is: the importance of a word increases in proportion to the number of times it appears in the text, but at the same time decreases in inverse proportion to the frequency with which it appears in the corpus. TF-IDF may effectively measure how important a word is in the context of a particular text. In some implementations, the TF-IDF for each word may be calculated using a variety of algorithms that have been currently developed. The scope of embodiments of the present disclosure is not limited in this respect.

In some embodiments, for each word in the text 102, a TextRank score for the word may also be calculated as a metric for evaluating the importance of the word to the text 102. TextRank is an algorithm for extracting keywords based on a graph, and the basic idea is to regard text as a network of words, and links in the network represent semantic relations between the words. For a given word, the TextRank algorithm calculates the importance of the given word based on the importance of the chains to other words of the given word.

In some embodiments, for each word in the text 102, the TF-IDF score of the word may also be combined (e.g., weighted) with the TextRank score of the word to obtain a combined score as a metric for evaluating the importance of the word to the text 102. The combined score not only considers the statistical characteristics of the words, but also considers the semantic relation among the words, so that the accuracy of extracting the keywords based on the combined score is higher.

In some embodiments, keywords 104 may also be extracted from text 102 based on past historical behavior of the user or other users. For example, words from text 102 having a semantic similarity to a predetermined word greater than a threshold may be selected as keywords 104 based on historical behavior of the user or other users with respect to the predetermined word. The historical behavior may include actions performed by the user or other user in the email application or other application that are related to the predetermined terms, such as the user or other user mouse clicking on the predetermined terms in the email application, copying the predetermined terms, the user or other user searching for the predetermined terms in other applications (e.g., a browser), and so forth.

For example, if a user has searched for a predetermined word on a website in the past, indicating that the user has been interested in the predetermined word in the past, the user is likely to be interested in words in the text 102 that are synonymous with the predetermined word. For another example, if a predetermined term is searched over the internet a number of times that a predetermined term has been suddenly increased (i.e., a threshold number of times is exceeded) over a predetermined period of time in the past, indicating that many users are interested in the predetermined term, then the current user is likely to also be interested in terms in the text 102 that have a synonymous relationship with the predetermined term. To this end, in some embodiments, a target word synonymous with the predetermined word may be selected directly from the text 102 as the keyword 104 without calculating a degree of importance of the target word to the text 102. In this manner, keywords 104 that may be of interest to the user are extracted from the text 102 based on historical behavior of the user or other users, thereby potentially providing more useful, targeted information to the user. In an embodiment of the present disclosure, a target word having a synonymous relationship with a predetermined word may be selected from the text 102 by calculating a semantic similarity between two words using a neural network.

For the text 102 shown in fig. 3, the keywords 104-1 "capturing", 104-2 "keyword", and 104-3 "presentation", etc. can be extracted therefrom by the above-described manner of determining the combined score of the TF-IDF score and the TextRank score of the word. It should be understood that although only three keywords are shown, the number of keywords may be any integer.

With continued reference to FIG. 2, at 204, the computing device 100 determines the user's interest in the keyword 104. The user's interest (i.e., interest or disinterest) in the keywords 104 relates to the prediction of the user's potential direction of interest. In some embodiments, the user's interest in the keywords 104 may be determined based on the type of keywords 104 or the occurrence of the keywords 104 in the collection of hotspot documents. Some embodiments of how to predict a user's interest in a keyword 104 are described in detail below.

In some embodiments, the user's interest in the keywords 104 may be determined by determining whether the keywords 104 are named entities. In the field of natural language processing, entities having a particular meaning are referred to as named entities, which mainly include names of people, places, organizations, proper nouns, and the like. In text such as e-mail, people tend to be more interested in entities of particular interest, and more like or need to know more information about these entities. To this end, named entity recognition techniques may be utilized to determine whether the extracted keyword 104 is a named entity. If the keyword 104 is a named entity, it may be determined that the keyword 104 is of interest to the user.

In some embodiments, the user's interest in the keyword 104 may be determined by determining whether the keyword 104 is a domain-specific term. Specific terms refer to a uniform definition of something specific to a particular field, often having a certain meaning in relation to its field. Persons unfamiliar with the art may need more information to help understand the specific meaning of this term accurately. Thus, if a keyword 104 is determined to be a domain specific term, it can be determined that the keyword 104 is of interest to the user. In the example of FIG. 3, specialized terms that are unfamiliar to the user (such as the keyword 104-1 "captioning") may appear in the text 102 of the email. In order to reply to the email with pertinence, the user may need to know the meaning of the term. In some embodiments, a term recognition technique may be utilized to determine whether the extracted keywords 104 are domain-specific terms.

In some embodiments, the user's interest in the keywords 104 may be determined by determining whether the keywords 104 are associated with a hotspot event. A hot event refers to an event that causes a wide range of concern over a predetermined period of time (e.g., a day, a week), and it is therefore often desirable to track the hot event and its progress. For example, keywords 104 in the text may be related to a recently occurring hotspot event, and the user may need to know the hotspot event before being able to better understand the contextual content of the text or to further process the text (e.g., reply to an email). It follows that keywords associated with a hotspot event may be keywords of interest to the user.

In some embodiments, to determine whether the keywords 104 are relevant to a hotspot event, it may be determined whether the extracted keywords 104 are present in a set of hotspot documents associated with the hotspot event, and the number of occurrences in the set of hotspot documents. If a keyword 104 exists in the collection of hotspot documents, indicating that the keyword 104 is associated with a hotspot event, it may further be determined that the keyword 104 is of interest to the user. Examples of a set of hotspot documents associated with a hotspot event may include, but are not limited to: documents that are searched in the search engine a number of times above a first predetermined threshold within a predetermined time range, documents that are clicked a number of times above a second predetermined threshold within a predetermined time range, and documents that are associated with the occurrence of a particular event within a predetermined time range. For example, a set of hotspot documents may include one or more documents that have been searched or clicked by a large number of users more than a predetermined number of times over the past hour, day, or week, one or more documents associated with a particular event organized by the progress of the particular event. The collection of hotspot documents may be obtained from a particular network resource, such as a news website.

Some embodiments of extracting keywords 104 and determining whether a user is interested in the keywords 104 are described above. It should be understood that such embodiments are merely illustrative. In some embodiments, the method for extracting keywords in the text 102 and the method for determining the user's interest in the keywords may be used interchangeably. For example, in one embodiment, the above-described method of determining a user's interest in a keyword may be utilized when extracting the keyword. Specifically, it is determined whether the words in the text 102 are named entities, domain-specific terms, and/or exist in the hotspot document set, and it is determined whether the words are keywords based on the result of the determination. Further, the above-described method regarding extracting keywords may be utilized when determining the interest of the user in the keywords. Whether a keyword is of interest to a user may be determined based on historical behavior (e.g., whether to click, copy, or search, etc.) of the user or other users for the keyword.

In this way, the determined keywords of interest to the user tend to coincide with the emphasis of interest of the user when reading text. Therefore, information more useful to the user can be further predicted on the basis of the keywords of interest.

With continued reference to FIG. 2, at 206, the computing device 100, in response to the user's interest in the keyword 104, generates the expanded information 106 associated with the keyword 104 without user intervention. According to an embodiment of the present disclosure, the generation of the expanded information is generated instantaneously by judging a keyword of interest in the text being presented by the application. If it is determined that the user is interested in a certain keyword or keywords 104, the expanded information 106 associated with such keywords 104 can be prepared directly in the application for the user without requiring the user to perform any additional actions with respect to the keyword 104 (such as clicking on a hyperlink related to the keyword, selecting or copying the keyword, clicking on an option in a drop-down menu, performing a search through a search tool, etc.). In some embodiments, the keywords 104 may be searched instantaneously on network resources such as encyclopedia websites, forums in professional areas, news websites, blogs, self media, etc., in response to determining that the keywords 104 are of interest to the user, to obtain expanded information 106 associated with the keywords 104.

In contrast to conventional methods, such as causing a user to be guided to the expanded information associated with the keyword in the form of a hyperlink in the text presented by the application or performing a manual search of the keyword by the user, in embodiments of the present disclosure, no additional operation or time is required by the user to obtain the expanded information, but rather the corresponding expanded information is automatically prepared for the user immediately depending on the actual text presentation and the interest of the individual user in the keyword. For example, in the case of hyperlinks, the mapping between a particular entry and the relevant extension information is already established in advance and cannot be supplied according to the personalized needs of the user. In the case of performing a search, a user also needs to copy a keyword with a tool such as a mouse and input the keyword into a search engine to perform the search, and the steps are various. In contrast, with the techniques of this disclosure, further information associated with the keyword may be prepared for the user without the user leaving the application and without any action needing to be taken with respect to the keyword. This provides more convenience and a better experience for the user.

In some embodiments, the generated expanded information may be related to the type of keyword 104 or the hotspot document in which the keyword 104 is located. In the case where the keyword 104 is a named entity, the generated expanded information associated with the keyword 104 may include, but is not limited to, an introduction to the keyword 104, a link to the introduction, and a summary of the introduction. Where the keyword 104 is a domain-specific term, the generated expanded information 106 associated with the keyword 104 may include, but is not limited to, a definition of the keyword 104, a link to the definition, and a summary of the definition. Where the keywords 104 are associated with a hotspot event, the generated extended information 106 associated with the keywords 104 may include, but is not limited to, a document (e.g., news) associated with the hotspot event, a link to the document, and a summary of the document. It should be understood that the extended information 106 may come from various network resources, such as encyclopedia websites, forums in professional areas, news websites, blogs, self-media, and the like. It should also be understood that the above-mentioned extended information 106 is merely exemplary, and other extended information associated with the keyword may also be generated according to actual needs.

At 208, the computing device 100 displays at least a portion of the generated extension information 106. In some embodiments, the computing device 100 may display a portion or all of the expanded information 106 in response to an indication by a user. For example, if it is determined that the user hovers a mouse over the keyword 104 or the user clicks on the keyword 104 with a finger or mouse, the computing device 100 may display a portion or all of the expanded information 106 associated with the keyword 104.

In some embodiments, the computing device 100 may automatically display the expanded information 106 without user intervention, also after generating the expanded information 106. In contrast to conventional approaches, such as prompting for the presence of expanded information in the form of a hyperlink in the text presented by an application or performing a manual search of keywords by a user, in embodiments of the present disclosure expanded information associated with keywords of interest to the user may be automatically generated and presented to the user without user intervention. In contrast, in a hyperlink scene, a user needs to click the hyperlink by using a mouse or other tools to obtain the presentation of the extension information; in the case of manual searching, the user requires more cumbersome steps to obtain search results associated with certain words in the text. In contrast, with the techniques of this disclosure, a user may more conveniently and directly obtain an extended information feed.

The expanded information 106 associated with the keywords 104 may be displayed in various ways. In some embodiments, such as in the case of an email application, these extension information 106 may be displayed in association with a reply to an email when the user creates the reply. In this way, the user can learn about information that may be helpful to the user to reply to the email while replying to the email. Such an extended information presentation manner is described below in conjunction with fig. 4 and 5.

Fig. 4 illustrates a GUI 400 presented by the email application in the case of replying to the email shown in fig. 3. For the original email shown in FIG. 3, the user creates reply email 410. In response to the creation of reply mail 410, expanded information 106 associated with keywords 104 of interest to the user in text 102 is displayed to the right of reply mail 410 in the form of page 420. The page 420 has presented thereon expanded information 106 associated with each keyword 104 of interest to the user, such as expanded information 106-1 associated with keyword 104-1 "capturing" and expanded information 106-2 associated with keyword 104-2 "avatar". Extension information 106-1 and extension informationInformation 106-2 may include information from different network resources related to "captioning" and "article," respectively. As shown in FIG. 4, extension information 106-1 may include a definition of a "clipping" related section from Wikipedia, a link to the definition "Closed Captioning- Wikepedia", an introduction from YouBube, or a portion thereof, a link to that introduction, of how to perform a" capture ""How to CaptionYouTube Videos-YouTube"and the like. Extension information 106-2 can include an introduction of how to use "article", a link to the introduction "Purdue OWL：How to Use Article(a/an/the)"and the like.

In some embodiments, if expanded information 106 related to multiple keywords 104 is to be presented, the display order of the expanded information 106 associated with each keyword 104 may be determined based on the score of each keyword 104 at the time the keyword is determined. For example, in the example shown in FIG. 4, since the score of the keyword 104-1 "capturing" is higher than the score of the keyword 104-2 "article", the expanded information 106-1 associated with the keyword 104-1 "capturing" may be displayed before the expanded information 106-2 associated with the keyword 104-2 "article".

In some embodiments, to facilitate quick browsing by the user to find the content of most interest to the user, the summary content may be displayed as the extended information 106 instead of the full content. The summary content is for example a part of a definition or introduction of a keyword, for example the first few sentences of the definition or introduction (as shown in fig. 4) or a summary of the definition or introduction. The summary content may also be, for example, a general description of a hotspot event, or the like.

In the case of only presenting the summarized content, the complete content associated with the summarized content may be displayed when the user hovers a mouse or hand over the summarized content in order to obtain the complete content. As shown in FIG. 5, only a portion 524 of the definition relating to "capturing" from Wikipedia is displayed. When the user hovers the mouse over the portion 524, the full content 526 associated therewith may be displayed. In this way, the user can conveniently and quickly browse the information from each network resource associated with each keyword, and pay attention to the interested content when needed, so that the user experience is improved.

In some embodiments, the summarized content and the link to obtain the complete content may also be displayed simultaneously as extended information (as in the example shown in FIG. 4). When the user clicks on the link, the user is directed to the relevant network resource to view the complete content. This facilitates the user to obtain more comprehensive information in the case of longer space of the complete content.

It should be understood that page 420 for presenting expanded information 106 may be displayed in association with reply email 410 in any layout, not limited to the layouts shown in fig. 4 and 5, according to actual needs. For example, page 420 may be displayed on the left, top, bottom, or any location convenient for the user to view in reply mail 410. The extension information 106 may also be presented in other orders. It should be understood that the expanded information 106 may also be displayed in association with the original email in response to the original email being opened.

In other embodiments, such as where the application presenting the text is a document editing application, keywords may be extracted from the text of the document and a determination may be made as to whether the keywords are of interest to the user. Display of extended information associated with the keywords of interest in association with the document may be in response to opening of the document, thereby enabling a user to obtain desired information without having to leave the document while browsing the document.

In other embodiments, such as where the application presenting the text is a browser, keywords may be extracted from the text on a web page presented by the browser and a determination may be made as to whether the keywords are of interest to the user. The expanded information associated with the keywords of interest may be displayed in association with the web page, such that the user may obtain the desired information (e.g., the progress of the hotspot event) without leaving the web page, without manually searching for the desired information.

It should be appreciated that only some examples of expanding the display of information in the case of different text presentations are given above. The presentation of the extension information may be designed in any other suitable way, according to the actual needs. Embodiments of the present disclosure are not limited in this respect.

Some example embodiments of the present disclosure are listed below.

In one aspect, there is provided a computer-implemented method comprising: extracting keywords from text presented by an application; determining whether the keyword is of interest to a user; in response to determining that the user is interested in the keyword, generating expanded information associated with the keyword without the user intervention; and displaying at least a portion of the extended information.

In some embodiments, displaying at least a portion of the expanded information comprises: displaying at least a portion of the expanded information without the user intervention.

In some embodiments, generating the expanded information associated with the keyword comprises: and searching the keywords to obtain the expanded information associated with the keywords.

In some embodiments, determining whether the keyword is of interest to the user comprises: determining whether the keyword is a named entity; and in response to the keyword being a named entity, determining that the user is interested in the keyword.

In some embodiments, determining whether the keyword is of interest to the user comprises: determining whether the keyword is a domain-specific term; and in response to the keyword being a domain-specific term, determining that the keyword is of interest to the user.

In some embodiments, determining whether the keyword is of interest to the user comprises: determining whether the keyword is present in a set of hotspot documents; and in response to the keyword being present in the collection of hotspot documents, determining that the keyword is of interest to the user.

In some embodiments, the set of hotspot documents includes at least one of: documents that are searched in the search engine a number of times above a first predetermined threshold within a predetermined time range, documents that are clicked a number of times above a second predetermined threshold within a predetermined time range, and documents that are associated with the occurrence of a particular event within a predetermined time range.

In some embodiments, the extension information comprises at least one of: an introduction of the keyword, a link to the introduction, a summary of the introduction, a definition of the keyword, the defined link, the defined summary, a target document in a set of hotspot documents in which the keyword is present, a link to the target document, and a summary of the target document.

In some embodiments, extracting the keywords from the text comprises: and selecting a target word with semantic similarity larger than a threshold value with the predetermined word from the text as the keyword based on the historical behaviors of the user or other users for the predetermined word.

In some embodiments, the historical behavior comprises actions performed by the user or the other user in the application or another application different from the application that are related to the predetermined terms.

In some embodiments, the application is an email application and the text is contained in a received email, and wherein displaying at least a portion of the expanded information comprises: in response to the user creating a reply to the email, displaying at least a portion of the expanded information in association with the reply.

In one aspect, an electronic device is provided, comprising: a processing unit; and a memory coupled to the processing unit and storing instructions that, when executed by the processing unit, perform the following: extracting keywords from text presented by an application; determining whether the keyword is of interest to a user; in response to determining that the user is interested in the keyword, generating expanded information associated with the keyword without the user intervention; and displaying at least a portion of the extended information.

In some embodiments, the set of hotspot documents comprises at least one of: documents that are searched in the search engine a number of times above a first predetermined threshold within a predetermined time range, documents that are clicked a number of times above a second predetermined threshold within a predetermined time range, and documents that are associated with the occurrence of a particular event within a predetermined time range.

In one aspect, a computer program product is provided that is tangibly stored in a non-transitory computer storage medium and includes machine executable instructions that, when executed by a device, cause the device to perform operations comprising: extracting keywords from text presented by an application; determining whether the keyword is of interest to a user; in response to determining that the user is interested in the keyword, generating expanded information associated with the keyword without the user intervention; and displaying at least a portion of the extended information.

The functions described herein above may be performed, at least in part, by one or more hardware logic components. For example, without limitation, exemplary types of hardware logic components that may be used include: field Programmable Gate Arrays (FPGAs), Application Specific Integrated Circuits (ASICs), Application Specific Standard Products (ASSPs), systems on a chip (SOCs), Complex Programmable Logic Devices (CPLDs), and the like.

Program code for implementing the methods of the present disclosure may be written in any combination of one or more programming languages. These program codes may be provided to a processor or controller of a general purpose computer, special purpose computer, or other programmable data processing apparatus, such that the program codes, when executed by the processor or controller, cause the functions/operations specified in the flowchart and/or block diagram to be performed. The program code may execute entirely on the machine, partly on the machine, as a stand-alone software package partly on the machine and partly on a remote machine or entirely on the remote machine or server.

In the context of this disclosure, a machine-readable medium may be a tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. The machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

Further, while operations are depicted in a particular order, this should not be understood as requiring that such operations be performed in the particular order shown or in sequential order. Under certain circumstances, multitasking and parallel processing may be advantageous. Likewise, while several specific implementation details are included in the above discussion, these should not be construed as limitations on the scope of the disclosure. Certain features that are described in the context of separate embodiments can also be implemented in combination in a single embodiment. Conversely, various features that are described in the context of a single embodiment can also be implemented in multiple embodiments separately or in any suitable subcombination.

Although the subject matter has been described in language specific to structural features and/or methodological acts, it is to be understood that the subject matter defined in the appended claims is not necessarily limited to the specific features or acts described above. Rather, the specific features and acts described above are disclosed as example forms of implementing the claims.

Claims

1. A computer-implemented method, comprising:

extracting keywords from text presented by an application;

determining whether the keyword is of interest to a user;

in response to determining that the user is interested in the keyword, generating expanded information associated with the keyword without the user intervention; and

displaying at least a portion of the extended information.

2. The method of claim 1, wherein displaying at least a portion of the expanded information comprises:

displaying at least a portion of the expanded information without the user intervention.

3. The method of claim 1, wherein generating expanded information associated with the keyword comprises:

and searching the keywords to obtain the expanded information associated with the keywords.

4. The method of claim 1, wherein determining whether the user is interested in the keyword comprises:

determining whether the keyword is a named entity; and

in response to the keyword being a named entity, determining that the user is interested in the keyword.

5. The method of claim 1, wherein determining whether the user is interested in the keyword comprises:

determining whether the keyword is a domain-specific term; and

in response to the keyword being a domain-specific term, determining that the user is interested in the keyword.

6. The method of claim 1, wherein determining whether the user is interested in the keyword comprises:

determining whether the keyword is present in a set of hotspot documents; and

in response to the keyword being present in the collection of hotspot documents, determining that the user is interested in the keyword.

7. The method of claim 6, wherein the set of hotspot documents comprises at least one of:

documents that are searched in the search engine a number of times above a first predetermined threshold within a predetermined time range,

documents having a number of clicks within a predetermined time range above a second predetermined threshold, an

Documents associated with the occurrence of a particular event within a predetermined time range.

8. The method of claim 1, wherein the extension information comprises at least one of:

an introduction of the keyword, a link to the introduction, a summary of the introduction, a definition of the keyword, the defined link, the defined summary, a target document in a set of hotspot documents in which the keyword is present, a link to the target document, and a summary of the target document.

9. The method of claim 1, wherein extracting the keywords from the text comprises:

and selecting a target word with semantic similarity larger than a threshold value with the predetermined word from the text as the keyword based on the historical behaviors of the user or other users for the predetermined word.

10. The method of claim 9, wherein the historical behavior comprises actions performed by the user or the other user in other applications different from the application that are related to the predetermined terms.

11. The method of claim 1, wherein the application is an email application and the text is contained in a received email, and wherein displaying at least a portion of the expanded information comprises:

in response to the user creating a reply to the email, displaying the at least a portion of the expanded information in association with the reply.

12. An electronic device, comprising:

a processing unit; and

a memory coupled to the processing unit and storing instructions that, when executed by the processing unit, perform the following:

extracting keywords from text presented by an application;

determining whether the keyword is of interest to a user;

displaying at least a portion of the extended information.

13. The apparatus of claim 12, wherein displaying at least a portion of the expanded information comprises:

14. The device of claim 12, wherein generating expanded information associated with the keyword comprises:

15. The apparatus of claim 12, wherein determining whether the keyword is of interest to the user comprises:

determining whether the keyword is a named entity; and

16. The apparatus of claim 12, wherein determining whether the keyword is of interest to the user comprises:

determining whether the keyword is a domain-specific term; and

17. The apparatus of claim 12, wherein determining whether the keyword is of interest to the user comprises:

determining whether the keyword is present in a set of hotspot documents; and

18. The apparatus of claim 12, wherein extracting the keywords from the text comprises:

19. The apparatus of claim 12, wherein the application is an email application and the text is contained in a received email, and wherein displaying at least a portion of the expanded information comprises:

20. A computer program product tangibly stored in a non-transitory computer storage medium and including machine-executable instructions that, when executed by a device, cause the device to perform operations comprising:

extracting keywords from text presented by an application;

determining whether the keyword is of interest to a user;

displaying at least a portion of the extended information.