KR101480411B1 - Method and system facilitating information searching on electronic devices - Google Patents

Abstract

A method and system for facilitating access to information via an electronic device, such as a CE device, comprising the steps of: obtaining information about a user's interest; identifying a user's potential data; Extracts data associated with the data of interest, and collects extracted relevant data for display to the user on the device, thereby enabling the user of the CE devices to have improved access to the Internet.

Information retrieval, Internet

Description

Field of the Invention [0001] The present invention relates to a method and system for facilitating information retrieval on an electronic device,

The present invention relates to providing appropriate information to a user, and in particular, to provide appropriate information to a user while reducing user input.

The Internet has become a popular source of entertainment and information. Most Internet content is designed to be accessed through a web browser, making it difficult to access through CE (Consumer Electronic) devices without a computer keyboard. As a result, the Internet is restricted to access on a PC or through a separate interface attached to the CE device.

As hardware and software technologies evolve, CE devices become more powerful. Increasing network infrastructure and lowering hardware prices have increased the number of entertainment devices that can use the network. Many users make up a home network that includes cable set-top boxes, digital TV sets, home media servers, digital audio players, and personal video recorders. Home network users also create, store and access more digital content via CE devices and PCs.

The second tendency to operate in parallel with the advent of networked entertainment devices is increasing the use of the Internet to create and distribute content. The wider spread of the broadband and lowering of the memory price allows the user to move large capacity files such as television shows or complete movies through the Internet.

However, there is a gap in the content on the digital content on the Internet and on networked entertainment devices in that most Internet content is organized and organized to access through a web browser rather than a typical CE device. For example, in general, a user searches for intuitive information by using a search engine or directly accessing a web site known through a PC. When a search engine is used, the user must generate an initial query, and then refine the query repeatedly according to the obtained result. In this way, it is necessary to understand and analyze a huge amount of information in order to accurately confirm / access the information the user wants to find. This process is effective on PCs, but the search / refinement process on CE devices without a keyboard and mouse is difficult and inconvenient. Also, users generally expect a 'lean-back' experience when users perform it using CE devices under their home and home networks. For example, a person watching television news on a television may not prefer to perform an internet search if more search effort is required than pressing a few buttons on the remote control.

Hereinafter, preferred embodiments of the present invention will be described in detail with reference to the accompanying drawings.

The present invention provides a method and system that facilitates accessing information through an electronic device, such as a CE device. One embodiment includes allowing users in the home to easily retrieve and access Internet content associated with content provided in a CE device. For example, a user can easily search for and access Internet content related to a program viewed on a TV. Now, while watching TV in your living room, you can access the appropriate information and video content on the Internet in a 'lean-back' state.

Information retrieval on the Internet generally involves two steps: search query formation and data retrieval and analysis. Query formation involves forming a search query that describes the type of information being searched. The data retrieval and analysis includes determining the search query according to the following steps. Identify the sources of candidate data. Appropriate data is extracted from such sources through search queries and then aggregated. Correlations regarding the type of assoaciation of consolidated data are verified to produce more meaningful results.

Hereinafter, a CE device implemented in a LAN (Local Area Network) such as a home network will be described. However, the present invention can be applied to other electronic devices, and can be applied not only to electronic devices in a LAN but also to electronic devices connected to the Internet. Figure 1 shows a functional block diagram of a network / system 10, such as a LAN of home devices, in accordance with an embodiment of the present invention. The network / system 10 includes devices such as an appliance 20, a personal computer 21, a CE device 30, which may include content, and a network / system 10, And an interface 40 for connecting to an external network 50 such as the Internet or the like. The external network 50 may be connected to one or more servers 51. The network / system 10 may implement other network communication protocols such as Universal Plug and Play (UPnP) or Jini, HAVi, IEEE 1394, and so on. The network / system 10 may be a wired network or a wireless network or a combination of the two. An example of a CE device includes digital devices such as DTVs, PDAs, media players, and the like.

The network / system 10 further includes a search facilitator system 24 that provides search, aggregation and analysis functions. Helper 24 performs query formation, data retrieval and analysis, and query formation includes classifying candidate search queries (i.e., candidate data of interest to the user) based on the user environment. Data retrieval and analysis also involves extracting, integrating, and correlating data of interest using an execution engine.

Figure 2 shows a structure 60 comprising a helper 24 in accordance with an embodiment of the present invention. The structure 60 according to an exemplary embodiment of the present invention implements a search, integration and analysis function through the helper 24 to provide information to a user through a user interface of the user module 64. For example, the user module 64 is implemented in a CE device such as the DTV 30. Referring to the flow diagram according to one embodiment of FIG. 3, in step 46, the helper 24 identifies the candidate data of interest to the user to make the user free from procedures related to query formation. In step 47, the user extracts data relating to the data of interest. In step 48, the extracted data are consolidated. In step 49, correlations of related data to be displayed to the user are established.

The information that the user is interested in or information associated with the user may include one or more of a user profile, user preferences, content that the user has previous / present access to, and terms previously selected by the user.

In one embodiment, the client module 64, including the following description, utilizes the helper 24 to obtain desired information (e.g., from the Internet) through a simple and intuitive graphical user interface (GUI) application .

1. Map functions supporting information retrieval to several numeric keys. For example, when the DTV 30 is used for information access, the function is mapped to several keys of the TV remote control 31 of FIG. 1 as an example for receiving a user input.

2. Allow users to express interest in obtaining additional information related to the information currently being accessed. For example, the user can press an "info" button on the remote 31 to map this action to a request for 'detailed information'.

3. If the user wishes to access the additional information, the user can indicate the specific type of the additional information to be searched. One example includes displaying a set of keywords associated with data that the user has expressed interest, such as TV programs or media content the user is accessing. Next, a combination of the up key / down key / right key / left key (up / down / right / left arr) keys on the remote controller 31 is provided so that the user can select one of the keywords as a search query.

4. A combination of the up key / down key / right key / left key on the remote control 31 to display a set of additional query suggestions associated with the selected keyword and to allow the user to select one of the query suggestions The user can refine or modify the proposed keyword / search query. The GUI allows the user to refine the search query as many times as desired by simply repeating the above-described process. It also displays a query suggestion in an editable text box that allows the user to delete existing characters or insert new characters to modify the query to the desired one. This can be performed, for example, by using a remote controller equipped with a wireless keyboard or a keypad.

5. Perform a search based on the formed query. Next, a list of search results corresponding to the keyword selected by the user is displayed so that the user can access the search result. Thereafter, a combination of the up key / down key / right key / left key on the remote controller 31 is provided to allow the user to select one of the refined search results. One example of a search result includes a link to a web page containing information about the search query, and the title of the web page is displayed to the user on the GUI.

The user uses the client module 64 to access specific content, and the helper 24 obtains information related to the accessed information for display to the user. Thereafter, the user requests the helper 24 to provide detailed information about the accessed content. For example, to request a helper 24 to provide detailed information about a previously recorded or broadcasted TV program that a user is viewing on a DTV 30 from an Internet data source 66, 64) is used.

Using the client module 64, a user can select, modify, or insert new queries, such as proposed keywords / categories, with minimal effort on a CE device that does not have a keyboard / mouse. In particular, helper 24 suggests and displays query terms including keywords associated with the TV program and information categories associated with such keywords. Using the proposed keywords and categories as search queries, the user can simply browse / search relevant information available on the Internet through his CE device by simply selecting among the proposed queries for search. Helper 24 classifies many appropriate search queries and allows the user to modify the proposed query or insert a new query. Thereafter, the helper 24 obtains information that the user is interested in and displays such information to the user.

In the structure shown in FIG. 2, the helper 24 includes a query determination unit 25 and a query determination unit 27 that implement the above-described steps. Specifically, the query confirmation unit 25 confirms the candidate data that the user is interested in. The query determining unit 27 extracts the identified candidate data that the user is interested from, for example, from the local source 69 and / or the Internet source 66, integrates the extracted data, And sets the correlation of the data. The operations of the query confirmation unit 25 and the query determination unit 27 will be described later.

In one example, the query confirming unit 25 confirms the candidate data that the user is interested based on the current application state of the user. The current application state refers to the state of the application that the user is using when the user wants to access the appropriate Internet content. For example, when the user is viewing a television program on the DTV 30, the channel tuned by the DTV and the program being broadcast can constitute the application status.

The query confirmation unit 25 confirms the content used / outputted by the application. Then, the query confirmation unit 25 acquires the metadata information and / or other data related to the content being accessed, and confirms the candidate search query that the user may be interested in. When the user accesses the content configured to use the metadata, the query confirmation unit 25 directly uses the field / value pairs from the metadata as candidate search queries. For example, if the user is viewing a music album of the musician "String " and is interested in accessing the related content, the query confirmation unit 25 extracts (content =" MusicAlbum & "Sting") field. The query confirmation unit 25 inferstates that the user may be interested in accessing more albums of the same musician and suggests (MusicAlbum, artist, "Sting") to the user as one of the search queries .

When a user accesses content such as a broadcast TV program or a DVD, the query confirmation unit 25 uses the caption data (closed captions) inherent in the stream to confirm the candidate search query. This inherent caption data includes information useful for forming a keyword. When the user wishes to access the related content while viewing the TV program, the query confirmation unit 25 analyzes the caption text of the TV program to identify an important keyword and proposes the candidate search query to the user.

The query verifying unit 25 may be implemented in an independent module or in a device 20 such as a set-top box or in a CE device 30 such as a DTV. A user interface (UI) may be displayed on a device in the network / system 10 capable of displaying information, such as a CE device. An example of analyzing the closed caption and confirming the keyword through the query confirmation unit 25 using NLP (natural language processing) to identify the keyword from the closed caption and suggesting the keyword as a candidate search keyword will be described below.

The closed caption (CC) of the TV program is embedded in the TV signal by the content provider before the broadcast starts. These are mainly for the hearing impaired. Extracting useful information from this text is not a simple matter. Captions generally do not include any case information and exclude any attempt to extract appropriate nouns based on case information. Also, because of the colloquial nature of the content, they often do not fit in the grammar, they can be misleading, and there may be typos. Due to these limitations, common keyword extraction techniques used in text documents may not be suitable for caption text. In addition, the caption content is highly dependent on the type of program. The caption of the news program is high-content and realistic. On the other hand, sitcom captions are generally low-content and slang. FIG. 4 shows a closed caption analyzer (CCA) 70 according to an embodiment of the present invention. The CCA 70 extracts a search query from the closed caption of the program using NPL technology and EPG information 75 to customize the extraction mechanism for various types of programs.

The CCA 70 operates in real time on the broadcast signal and processes a regular stream 74 of caption text coming into the system. The CCA runs two history windows over the stream of text being entered (Figure 5). The smaller most recent window corresponds to the last N sentences Si (N = 5 in this embodiment) and the larger program wide window corresponds to the entire TV program / Current news story / current program section. Only the keywords extracted from the 'program wide window' are stored and indexed for recommendation. Also, in order to display the most recent keywords at the top of the list of keywords displayed to the user, the keywords extracted from the 'most recent window' have a higher ranking than others. As soon as the program or news story changes, the individual windows are initialized and restarted. The change is determined by special characters in the caption ('>>>' in the US) or by checking the EPG and current time.

The CC Tokenizer 78 receives the stream 74 of CC text and divides it into sentences. This is done to preserve the grammar of the text. Next, a tagger 73 adds a tag to the sentences. For example, Brill's part of speech tag is added (Brill 1992). Tagger 73 analyzes the sentence to determine how each word is used in the sentence. The tagger 73 uses a dictionary rule to assign an initial tag to each word in a sentence and then uses a contextual rule to update the tag based on the context in which the word is used. Contextual rules are sensitive to the grammar of the input sentence. Incorrect or incomplete sentences may result in incorrect tags being added to words in the sentence.

For example, the output of the tag 73 with respect to the input sentence "John Wayne ran home" may be "John <PROP> Wayne <PROP> ran <VB_PST> home <NOUN> '.

In the previous sentence, "John" and "Wayne" are used as proper nouns, "ran" is a past verb and "home" is a noun.

The tagged sentence is transmitted from the tag 73 to the rule engine 79. The rule engine 79 extracts a keyword from the tag to which the tag is added, based on an extraction policy rule from the rule library 71. The rule library (R) 71 identifies a set of rules that can be used to extract various kinds of phrases that are present in a sentence. The law is expressed in tag patterns. For example, you may have a rule for extracting consecutive proper nouns (<PROP> +), and other rules (<ADJ> + <NOUN> +) that extract consecutive adverbs from one or more nouns . The rule selector 72 includes mapping a genre to an extraction policy. The genre of the program being watched determines the type of keywords to be extracted from the captions. For example, if the program being watched is a high-content and realistic program, such as news, the extraction policy is very aggressive and it is necessary to add an additive that distinguishes the types of keywords, such as a series of nouns, compound nouns, proper nouns, . On the other hand, if the program is a low-content and non-realistic program, such as a sitcom, then a very conservative extraction policy that extracts only those keywords that are very selective in extracting keywords and considered to be more practical, such as proper nouns, do. The rule engine 79 changes the extraction habit according to the type of program being watched.

Each extraction policy (Pe) corresponds to a subset of the rules in R. The mapping can be preset or obtained. The mapping essentially defines the type of pattern to be used to extract the keywords 76 from a program of a particular genre (type). In one example, the mapping includes a small user study associated with the four topics requested to display the keywords they are searching for from the CC copy of the four types of sample programs: news, sitcoms, talk shows, Can be determined. The copy is tagged using Brill's tag, and tags of displayed keywords are extracted according to the rule. For example, if the keyword "Global Warming" is displayed in a news program and a tag such as "Global <ADJ> Warming <NOUN>" is added to the word, "<ADJ> <NOUN> And is extracted in accordance with the rule for. The top ranked rules (based on frequency and threshold) are used as a rule to form an extraction policy for that type of program, and a set of all rules for all types of programs form R. This facilitates reusability of rules and extraction policies. The rule engine 79 applies an extraction policy to the text received from the tagger 73 and extracts keywords from it. Thereafter, these keywords are weighted based on whether they appear in the "most recent window ". The weighted keywords are sorted and displayed to the user.

The extracted keywords are regarded as candidate information that the user is interested in. The query determining unit 27 extracts data related to the candidate data that the user is determined to be interested in, integrates the extracted data, and establishes a correlation of the integrated data. Such a correlation involves confirming the association between the data. For example, data A is &quot; similar &quot; or &quot; same &quot;

The query determining unit 27 may be implemented in an independent module, in a device 20 such as a set-top box, or in a CE device 30 such as a DTV. An example of implementing data extraction, integration and correlation setup by a query decision unit 27 using a query plan will be described below. An XML-based execution plan is provided that encapsulates the steps associated with the search query decision process. An execution plan includes one or more plan-steps and each planning step essentially specifies the type of work to be performed, such as data extraction, integration, or correlation setup.

In addition, specific groups, referred to as RuleLets, are provided to perform three tasks: data extraction, collection, or correlation establishment in a general query determination process. Roulettes include 'GetDataRuleLet', 'MergeDataRulet' and 'GetContentNotInHomeRuleLet'. 'GetDataRuleLet' acquires data from various data sources, 'MergeDataRulet' merges data obtained from various data sources, 'GetContentNotInHomeRuleLet' is data / content that is not available in the home device &Lt; / RTI &gt;

The planning step essentially specifies the set of input and output parameters required for the execution of the roulette and roulette to be executed. The specific fields in the planning phase include the name of the roulette to be executed, the input data required for the execution of the roulette, the type of output predicted from the execution of the roulette, and the range in which the output data is required (applicable). The range field indicates whether the requested data should be available in the Local or the Internet. In order to satisfy various kinds of search queries, a planning library including various kinds of plans is operated. When the user selects a search query, the query determining unit 27 determines whether or not a plan is selected based on the user &apos; s environment, such as whether the user is watching a TV program, a DVD or a music video, .

An example of using an execution plan on a search scenario combined with execution plans is described below. The search scenario relates to a case where a user watches a documentary program broadcast titled "Drumming Techniques " via TV. If the user is interested in accessing the associated Internet content, the search helper 24 confirms and displays the candidate search query from the closed caption of the program by executing the following planning steps. And acquires the EPG related to the TV program that the user is watching. The keyword is acquired from the EPG information acquired in the previous step. Check the genre of the TV program. And obtains important keywords from the caption of the TV program based on the genre. Then, the keywords identified from the EPG and the closed caption are merged. An example of an XML version of the above-described plan is as follows.

<? xml version = "1.0"?>

<Plan>

<Plan-step>

<RuleLet> GetDataRule </ RuleLet>

<OutputType> EPGInfo </ OutputType>

<Scope> Internet </ Scope>

       </ Plan-step>

 <Plan-step>

<RuleLet> GetDataRule </ RuleLet>

<InputType> EPGInfo </ InputType

<OutputType> KeywordsFromEPG </ OutputType>

<Scope> Local </ Scope>

       </ Plan-step>

       <Plan-step>

<RuleLet> GetDataRule </ RuleLet>

<OutputType> ProgramGenre </ OutputType>

<Scope> Local </ Scope>

       </ Plan-step>

       <Plan-step>

<RuleLet> GetDataRule </ RuleLet>

<InputType> ProgramGenre </ InputType

<OutputType> KeywordsFromCaptions </ OutputType>

<Scope> Internet </ Scope>

       </ Plan-step>

       <Plan-step>

<RuleLet> MergeDataRule </ RuleLet>

<InputType> KeywordsFromEPG </ InputType>

<InputType> KeywordsFromCaptions </ InputType>

<OutputType> LiveTVKeywords </ OutputType>

<Scope> Local </ Scope>

       </ Plan-step>

</ Plan>

The keywords obtained by executing the above-described plan are displayed to the user. One of the displayed keywords / candidate search queries is "Polyrthymic Drumming ". The user selects "Multiple rhythm drums" and sees more relevant images that the user has not previously watched. In order to solve such a request, the helper 24 executes a plan including the following steps with "multiple rhythm drums" set as keywords. And acquires available videos on the Internet source (66 in FIG. 2) associated with the "multi-rhythm drummer" keyword. Identify videos available in previously recorded homes related to "multi-rhythm drums." And filters previously used videos in the local source 69 in the resulting list after performing the previous step. An example of an XML version of the above-described plan is as follows.

 <? xml version = "1.0"?>

<Plan>

       <Plan-step>

<RuleLet> GetDataRule </ RuleLet>

<InputType> Keyword </ InputType

<OutputType> RelatedVideos </ OutputType>

<Scope> Internet </ Scope>

       </ Plan-step>

       <Plan-step>

<RuleLet> GetDataRule </ RuleLet>

<InputType> Keyword </ InputType>

<OutputType> RecordedVideos </ OutputType>

<Scope> Local </ Scope>

       </ Plan-step>

       <Plan-step>

<RuleLet> GetContentNotInHomeRule </ RuleLet>

<InputType> RelatedVideos </ InputType>

<InputType> RecordedVideos </ InputType>

<OutputType> InternetVideosNotInHome </ OutputType>

<Scope> Local </ Scope>

       </ Plan-step>

</ Plan>

Related Internet videos that were previously unavailable in the local source 69 are displayed to the user on the client module.

FIG. 6 illustrates a functional block diagram 80 of a helper system implemented in a context-specific search facilitator system (CSF) 82 according to an embodiment of the present invention. The CSF 82 provides a query determination function such as keyword extraction and a query determination function such as data extraction, integration, and correlation setting as described above. The CSF 82 includes various layers to allow continuous retrieval and access to CE device content and Internet content from the data sources 81.

The CSF 82 includes a data and query processing (DQP) layer 83. The DQP 83 helps determine the user query and also provides an API for client applications to make use of it. The client applications 64 are shown outside the CSF 82, but may be included as a component of the CSF 82. DQP 83 includes a query execution planner (QEP) 84 and an information source manager (ISM) The CSF 82 further includes a data excution (hereinafter DE) layer 86. The DE 86 includes a data extraction manager (DEM) 87 and a plurality of plug-ins 88.

QEP 84 provides an interface for client applications for retrieving and accessing related data available on the Internet and locally available data (i.e., data stored in device 30 and / or device 20). The QEP 84 operates a planning library 89 that contains a predetermined execution plan to be used to resolve the data request. The QEP 84 operates the roulette (90) classes that are executed as part of the plan. When the QEP 84 receives a query from the client application, the QEP 84 obtains the appropriate plan from the planning library 89 and executes it. During execution of the plan, QEP 84 obtains the requested information / content (via ISM 85) by the user using plug-ins 88 in data extraction layer 86. The ISM 85 manages a directory containing detailed information about the type of data that each data extraction plug-in component can extract and the type of input data predicted by the plug-in 88 to do so. This allows the QEP 84 to verify the plug-in 88 that provides the specific type of data

DE 86 includes many plug-ins 88 for extracting content / information from local and Internet data sources 81. Local data sources refer to, for example, home devices. Internet data sources include seed sources such as 'BarnesandNoble.com, Youtube.com' and Internet search engines such as 'Google, Yahoo'. The functions provided by the various plug-ins 88 include the following. (1) The Web scraper plugin allows you to extract specific information from specific Web sites. (2) The Content Manager plug-in allows access to media content stored on home devices. (3) The Internet Video Search plug-in allows browsing or accessing video content on the Internet. (4) Caption Analysis Plug-in allows you to analyze and classify keywords from TV captions. (5) The EPG plug-in enables EPG information to be obtained from TV programs.

The DE 86 manages the plug-ins 88, provides an application programming interface to allow new plug-ins 88 to be inserted or removed through minimal code changes, and enable higher-level components to use plug-ins do.

As an example of the search assistance process by the CSF 82 according to the present invention, a TV viewer accessing the Internet is as follows. User Trisha watches TV programs on "Drumming Technology" on her TV, which is accomplished by video. She wants to know more about the topics covered in this program. In particular, I would like to know about the "multi-rhythm drums" just mentioned. She presses the TV remote control 31 and searches for a host of information about the program being watched. The UI graphics on the client module screen provide two menus. One menu 64A provides a list of keywords associated with the TV program collected by the query verifier of the CSF 82 and a highlight is placed in the first keyword "Multiple rhythm drums ". The other menu 64B shows a list of search results including a web link containing information and / or videos associated with the keyword "multi-rhythm drums ". The search result is collected by the query determiner of the CSF 82. Trish confirms that the second link on this menu is "how" video. Use the navigation buttons on the remote control to move the highlight to this link, and press the Select button to select and listen to the video.

The scenario described above describes the following essential features. First, the user does not need to input text or query at any point. The interaction is via a search button on a conventional remote control. Second, the user can access the desired related Internet information by pressing a few buttons without having to enter a search page or a search word. In such a scenario, the user's environment, such as the program that is being watched, helps to search for appropriate content.

The process of providing appropriate information to a user of a CE device on a local network, such as a home network, generally includes:

1. Gather information about your current activities on your local network, such as listening to music or watching TV programs.

2. Collect situational information about the user's activity on the local network, such as retrieving the song's metadata or retrieving the metadata of the TV program.

3. Obtain additional information that is closely interrelated with the information obtained by the above-described steps from information from other sources such as devices on the local network and / or from external sources such as the Internet. For example, information related to a song or TV program is obtained.

4. Confirm the correlation of the information obtained in the above step.

5. Use correlations in forming queries to retrieve information in an external source, such as a region or / and the Internet.

6. The search results are displayed to the user with information related to the current user's activities (ie, information that the user is interested in).

Confirmation of the correlation can be performed by one or more of the following methods.

(1) Verify the correlation between information about the user's current activity and closely related information obtained from local sources.

(2) Verify the correlation between information about the current user's activities and closely related information obtained from external sources.

(3) Identify correlations between information related to current user activity and closely related information obtained from local and external sources.

It supports a function to map information retrieval to several keys in order to minimize the number of keys the user has to input in order to receive information related to the user's current activity. As an example, map the search to the keys on the remote control. Specific information about the user's activity on the CE device is then obtained. This involves obtaining metadata contained in media accessible only by the CE device rendering the content. For example, the length and type of content included in the CE or DVD.

The process may further include obtaining information inherent in a broadcast stream accessible only by the receiving / rendering CE device. For example, subtitles and captions. In addition, information about content already existing on the home network is obtained. For example, it is the song and metadata of the Sting that the user already owns. In addition, information about appropriately structured data present on the Internet is obtained. For example, it acquires metadata about a song that the user already owns from a CD database (compact disk database, CDDB). Additional appropriate information is obtained from the partially structured data present on the Internet. For example, it acquires the biographies of musicians from an internet movie database (IMDB) and / or an appropriate web page. It also obtains appropriate information from unstructured information that exists on the Internet. For example, it is the address of a web page that conveys geographical, economic, political, and cultural information about a location from the main events reported in the news.

The collected / obtained information defines information at hand. Next, when the user operates the CE device, a correlation is established between the information that the user inputs to the CE device and information that can be used immediately, in order to automatically perform the query formation for retrieving the related information. This minimizes the need for the user to create a query or minimizes the use of the keyboard to generate the query.

Next, a correlation is established between the data extracted from the Internet source and the data extracted from the home network content in order to settle the query for accurate retrieval from the immediately available information. The query plan is executed to retrieve queries on the external network, such as the Internet or other resources, without requiring user input. The query execution result is displayed to the user in the form of a search result. Preferably, the most appropriate information from the search results is selected to be presented to the user based on the readily available information without requiring the user's input. Therefore, the information to be displayed to the user includes candidate information that the user is interested in, which is related to information that can be immediately used.

Other examples of tidal searching for a user include obtaining information related to the user's current activity on the local network, obtaining contextual information about the user's activity on the local network, Acquiring closely related related information, acquiring correlation between additional information, environmental information, and user activity information, and using correlations to form a query to retrieve information related to the user's current activity .

Obtaining additional information may include obtaining additional information closely related to contextual information from sources including the local network and / or external sources, and obtaining additional information closely related to user activity information. Confirming the correlation may involve identifying the correlation between the information about the user's current activity and the closely related information obtained from the local sources. Confirming the correlation may involve identifying a correlation between information about the user's current activity and closely related information obtained from external sources. Confirming the correlation can include identifying information about the user's current activity and correlating closely related information obtained from local and external sources.

Formulating a query involves forming a query automatically without a user input request. The query is executed to obtain a search result containing information related to the user &apos; s current activity. Executing the query includes executing a query to retrieve relevant information on the local network and / or external sources. The search results are shown to the user at this stage through a user interface within the device, such as a CE device.

Obtaining information about the user's current activity on the local network includes obtaining information from user input to the device, and obtaining information from applications running on the network. Obtaining additional information may include obtaining additional information from external structured data sources. Obtaining additional information includes obtaining appropriate additional information of interest to the user from local media content sources.

Obtaining additional information may include obtaining additional information from external non-organized data sources, obtaining information from external, semi-structured data sources, obtaining information from external broadcast data sources And acquiring the information.

Obtaining contextual information regarding current user activity within the local network may include obtaining relevant metadata available on the local network. As such, forming a query may include using metadata associated with the content on the local network to determine the situation for query formation. In addition, determining the context for query formation may include utilizing metadata from the application on the local network and metadata associated with the content in the network without requiring the user to input. The query can be used to search the Internet for information related to the user's current activity or interest. As such, the above-described processes can also enable a user of the CE devices to have improved access to the Internet.

Those skilled in the art will appreciate that one structure according to the present invention may be implemented as a program instruction executed by a processor, a program medium stored in a computer-readable medium, a computer implemented method, , An integrated circuit describing an application, firmware, and the like. Although the present invention has been described in terms of a usable range with reference to a preferred specific version, other versions are also possible. Accordingly, the scope and spirit of the appended claims should not be limited to the description of the preferred version contained herein.

The above-described embodiments of the present invention can be embodied in a general-purpose digital computer that can be embodied as a program that can be executed by a computer and operates the program using a computer-readable recording medium.

The computer readable recording medium may be a magnetic storage medium such as a ROM, a floppy disk, a hard disk, etc., an optical reading medium such as a CD-ROM or a DVD and a carrier wave such as the Internet Lt; / RTI &gt; transmission).

The present invention has been described with reference to the preferred embodiments. It will be understood by those skilled in the art that various changes in form and details may be made therein without departing from the spirit and scope of the invention as defined by the appended claims. Therefore, the disclosed embodiments should be considered in an illustrative rather than a restrictive sense. The scope of the present invention is defined by the appended claims rather than by the foregoing description, and all differences within the scope of equivalents thereof should be construed as being included in the present invention.

Thereby allowing the user of the CE devices to have improved access to the Internet.

Figure 1 illustrates a network implementing a method for enabling a user to facilitate information retrieval in accordance with an embodiment of the present invention.

FIG. 2 shows an embodiment of a structure for facilitating information retrieval according to the present invention.

Figure 3 shows a flow diagram of the overall steps associated with a method for facilitating information retrieval in accordance with the present invention.

FIG. 4 shows an embodiment relating to keyword selection according to the present invention.

FIG. 5 shows an embodiment of torque-reducing according to the present invention.

6 shows an embodiment of a structure for facilitating a search using an execution plan according to the present invention.

One embodiment of the present invention includes: obtaining information about user interests; Identifying potential data of interest to the user; Extracting data related to the data the user is interested in; And collecting related data extracted for display to the user on the device.

Wherein the step of verifying candidate data of interest by the user comprises: monitoring user access to content; Selecting a set of extraction rules for extracting information; And extracting key information from the metadata about the content based on the selected extraction rule.

The step of selecting the set of extraction rules may further comprise selecting a set of extraction rules based on the type of the content.

Wherein the step of selecting a set of extraction rules further comprises selecting a set of extraction rules from a rule library based on the content type, the rule library comprising a list of rules for extracting various keywords . &Lt; / RTI &gt;

Obtaining information about the user's interests may include obtaining information about the user's current activity on the device.

The step of acquiring information on the user's interests may further comprise acquiring contextual information on the current activity of the user on the local network.

And correlating the related data to be displayed to the user.

The step of extracting data associated with the data of interest to the user may include forming a query to search the related data based on a candidate of data of interest.

And executing a query to retrieve related information from at least one of the local network and an external source.

The device may comprise a CE device.

The step of executing the query may include searching the Internet for the related data.

According to another aspect of the present invention, there is provided an information processing apparatus including an information collecting unit configured to check information on a user interest; A confirmation unit configured to identify candidate data of interest by the user; An extracting unit configured to extract data related to the data that the user is interested in; And a collection unit configured to collect the extracted related data for display to the user on the device.

Claims (25)

A method for allowing a user of a device to easily retrieve information, Obtaining information about a user interest; Identifying potential data of interest to the user; Extracting data related to the data the user is interested in; And Collecting the extracted related data for display to the user on the device, Wherein the step of verifying candidate data of interest by the user comprises: Monitoring user access to content; Selecting a set of extraction rules for extracting information; And Extracting key information from the metadata related to the content based on the selected extraction rule, wherein the extracted key information is weighted to the key information based on whether or not the extracted key information appears in the most recent window &Lt; / RTI &gt; delete 2. The method of claim 1, wherein selecting the set of extraction rules comprises: Further comprising selecting a set of extraction rules based on the type of the content. 4. The method of claim 3, wherein selecting the set of extraction rules comprises: Further comprising selecting a set of extraction rules from a rule library based on the content type, Wherein the rule library includes a list of rules for extracting various keywords. 2. The method of claim 1, wherein obtaining information about the user &apos; And obtaining information about the current activity of the user on the device. 6. The method of claim 5, wherein obtaining information about the user's interests comprises: Further comprising obtaining contextual information regarding the current activity of the user on the local network. The method according to claim 1, Further comprising the step of correlating said related data to be displayed to said user. The method of claim 1, wherein extracting data associated with the data of interest to the user comprises: And forming a query to search the related data based on a candidate of data of interest. 9. The method of claim 8, Further comprising executing a query to retrieve relevant information from at least one of a local network and an external source. 10. The apparatus of claim 9, &Lt; / RTI &gt; CE device. 11. The method of claim 10, wherein performing the query further comprises: And searching the Internet for the associated data. An apparatus for allowing a user of a device to easily retrieve information, An information collecting unit configured to check information on a user interest; A confirmation unit configured to identify candidate data of interest by the user; An extracting unit configured to extract data related to the data that the user is interested in; And And a collection unit configured to collect the extracted related data for display to the user on the device, The verification unit monitors the user access to the content, selects a set of extraction rules for information extraction, extracts key information from the metadata about the content based on the selected extraction rule, Lt; RTI ID = 0.0 &gt; candidate data, Wherein the extracted key information is weighted to the key information based on whether the extracted key information appears in the most recent window. delete 13. The apparatus according to claim 12, And to select a set of extraction rules based on the content type. 15. The apparatus according to claim 14, And to select a set of extraction rules from a rule library based on the content type, Wherein the rule library includes a list of rules for extracting various keywords. The information processing apparatus according to claim 12, And obtain information about the user's interest on the device by obtaining information about the user's current activity on the device. The information processing apparatus according to claim 16, And to obtain information about the user's interests by obtaining contextual information about the user &apos; s current activity on the local network. 13. The apparatus according to claim 12, And to correlate the related data to be displayed to the user. 13. The apparatus according to claim 12, And form a query for retrieving the related data based on a candidate of data of interest. 20. The apparatus according to claim 19, And execute a query to retrieve relevant information from the local network or from an external source. 21. The apparatus of claim 20, &Lt; / RTI &gt; CE device. 22. The apparatus of claim 21, And to search the Internet for the associated data. A system for allowing a user to easily retrieve information, A device for accessing content; And Includes a facilitator, Preferably, An information collecting unit configured to check information on the user interest; A confirmation unit configured to identify candidate data of interest by the user; An extracting unit configured to extract data related to the data that the user is interested in; And And a collection unit configured to collect the extracted related data for display to the user on the device. A computer-readable recording medium on which a program for executing the method according to claim 1 is recorded. A computer-implemented method for allowing a user of a device to easily retrieve information, Obtaining information about a user interest; Identifying candidate data of interest by the user; Extracting data related to the data the user is interested in; And Collecting the extracted related data for display to the user on the device Wherein the step of verifying candidate data of interest by the user comprises: Monitoring user access to content; Selecting a set of extraction rules for extracting information; And Extracting key information from the metadata related to the content based on the selected extraction rule, wherein the extracted key information is weighted to the key information based on whether or not the extracted key information appears in the most recent window &Lt; / RTI &gt;

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