KR20090107402A - Method and system facilitating information searching on electronic devices - Google Patents

Abstract

PURPOSE: A method for easily searching information in an electronic device and a system thereof are provided to enable users of CE devices to easily access the Internet. CONSTITUTION: A method for enabling a user of a CE device to easily search information comprises the following steps of: obtaining information about a concern of the user; confirming candidate data which the user is interested in(46); extracting data related to the data in which the user is interested(47); and collecting the extracted data to display it on the device(48).

Description

Method and system facilitating information searching on electronic devices

The present invention relates to providing appropriate information to a user, and in particular to providing appropriate information to the user with reduced 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, which makes it difficult to access through Consumer Electronic (CE) devices that do not have 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 develop, CE devices become more powerful. Increasing network infrastructure and falling hardware prices have increased the number of entertainment devices that can use the network. Many users are building home networks that include cable set-top boxes, digital TV sets, home media servers, digital audio players, and personal video recorders. In addition, home network users are creating, storing and accessing more digital content through CE devices and PCs.

A second trend that works in parallel with the emergence of networked entertainment devices is increasing the use of the Internet to create and distribute content. The proliferation of wider broadband and falling memory prices allow users to move large files over the Internet, such as television shows or complete movies.

However, there is a gap between digital content on the Internet and content on networked entertainment devices in that most Internet content is organized and organized for access through a web browser rather than a typical CE device. For example, a user typically retrieves information by using a search engine or by directly accessing a known website through a PC. In the case of using a search engine, the user must generate an initial query, and then refine the query repeatedly according to the obtained result. As such, in order to accurately identify / access the information desired by the user, a huge amount of information must be understood and analyzed. While this process is effective on PCs, the search / purification process on CE devices without keyboards and mice is difficult and inconvenient. In addition, the user generally expects a 'lean-back' experience if the user performs it using a CE device under their home and home networks. For example, a person watching television news on television may not prefer to do an Internet search if more search effort is needed than to press a few buttons on the remote control.

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

The present invention provides a method and system that facilitates access to 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 by the CE device. For example, a user may easily search for and access Internet content related to a program he / she is watching on a TV. Now you can access the appropriate information and video content on the Internet in the 'lean-back' while watching TV in your living room.

Information retrieval on the Internet generally involves two phases: search query formation and data retrieval and analysis. Query formation involves forming a search query that describes the type of information to be retrieved. Data retrieval and analysis involves determining a search query according to the following steps. Identify the sources of candidate data. Appropriate data is extracted from such sources through search queries, which are then aggregated. In order to produce more meaningful results, a correlation of the type of association among the consolidated data is identified.

Hereinafter, a CE device implemented in a local area network (LAN) such as a home network will be described. However, the present invention can be applied to other electronic devices, and can be applied to electronic devices connected to the Internet, not just electronic devices in a LAN. 1 illustrates 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. Network / system 10 may include devices such as appliances 20, personal computers (PCs) 21, CE devices 30 that may contain content, and network / systems 10 to other local networks. Or an interface 40 for connecting to an external network 50, such as the Internet. The external network 50 may be connected to one or more servers 51. The network / system 10 may implement Universal Plug and Play (UPnP) or other network communication protocols such as Jini, HAVi, IEEE 1394, and the like. The network / system 10 may be a wired network or a wireless network or a combination of both. Examples of CE devices include 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 functionality. The assistant 24 performs query formation, data retrieval and analysis, which includes classifying candidate search queries (ie, candidate data of interest to the user) based on the user environment. Data retrieval and analysis also includes the use of execution engines to extract, integrate and correlate data of interest.

2 shows a structure 60 comprising an assistant 24 in accordance with one embodiment of the present invention. The structure 60 according to one embodiment of the invention implements the search, integration and analysis functions through the helper 24 to provide information to the user through the user interface of the user module 64. As an example, the user module 64 is implemented in a CE device such as the DTV 30. Referring to the flowchart in accordance with one embodiment of FIG. 3, at step 46, the assistant 24 identifies candidate data of interest to the user to free the user from procedures associated with query formation. In step 47, data related to data of interest to the user is extracted. In step 48, the extracted data are integrated. In step 49, a correlation of related data to be displayed to the user is established.

Information that the user is interested in or related to the user may include one or more of a user profile, user preferences, content previously / currently accessed by the user, and terms previously selected by the user.

In one embodiment, the client module 64, which includes the following description, utilizes an assistant 24 to obtain desired information (eg from the Internet) through a simple and intuitive graphical user interface (GUI) application. .

1. Map a function that supports information retrieval to several numeric keys. For example, when using the DTV 30 for information access, an example for receiving a user input is to map such a function to several keys of the TV remote control 31 of FIG.

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

3. When the user wants to access the additional information, the user can indicate the specific type of the additional information to search. For example, the method may include displaying a set of keywords related to data expressing interest by the user, such as a TV program or media content that the user is accessing. Next, a combination of up / down / right / left arrwo keys is provided on the remote controller 31 to allow the user to select one of the keywords as a search query.

4. A combination of up / down / right / left keys on the remote control 31 to display a set of additional query suggestions that include or are associated with the selected keyword and allow the user to select one of the query suggestions. As it provides, 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 process. It also displays query suggestions in an editable text box that allows the user to delete existing characters or insert new characters to modify the query as desired. This may be performed by using a remote controller having a wireless keyboard or a keypad as an example.

5. Perform a search based on the formed query. Next, the user may access the search result by displaying a list of search results corresponding to the keyword previously selected by the user. Thereafter, a combination of an up key / down key / right key / left key on the remote controller 31 is provided for the user to select one of the refined search results. One example of a search result includes a link to a web page that includes information about the search query, wherein 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 assistant 24 obtains information related to the information accessed for display to the user. The user then asks the assistant 24 to provide detailed information about the accessed content. For example, in order to request that the assistant 24 provide detailed information about a pre-recorded or broadcast TV program that the user is watching on the DTV 30 from the Internet data source 66, the user may request a client module ( 64).

Using the client module 64, a user can select, modify or insert new queries such as keywords / categories proposed with minimal effort on a CE device without a keyboard / mouse. In particular, the assistant 24 suggests and displays query terms including keywords associated with the TV program and categories of information associated with those keywords. Using the proposed keywords and categories as a search query, a user can constantly browse / search the relevant information available on the Internet through his CE device by simply selecting from the suggested queries for search. The assistant 24 categorizes many suitable search queries and allows the user to modify the proposed query or insert a new query. The assistant 24 then obtains the information of interest to the user and displays that information to the user.

In the structure shown in FIG. 2, the assistant 24 includes a query identification unit 25 and a query determination unit 27 implementing the above-described steps. Specifically, the query confirmation unit 25 confirms candidate data of interest to the user. The query determination unit 27 extracts the identified candidate data of interest to the user from, for example, the local source 69 or / and the Internet source 66, etc., integrates the extracted data, and collects it for display to the user. Correlate the generated data. The operation of the query confirmation unit 25 and the query determination unit 27 will be described later.

In one example, the query confirmation unit 25 identifies candidate data of interest to the user based on the current application state of the user. The current application state refers to the state of the application being used by the user at the time the user wants to access appropriate Internet content. For example, when a user is watching a television program on the DTV 30, the channel tuned by the DTV and the program being broadcast may configure the application state.

The query confirmation unit 25 confirms the content used / output by the application. Thereafter, the query confirmation unit 25 obtains metadata information and / or other data related to the content being accessed and identifies a candidate search query that may be of interest to the user. When a user accesses content configured to use metadata, the query checker 25 directly uses the field / value pairs from the metadata as candidate search queries. For example, if a user is listening to a music album of the artist "String" and expresses interest in accessing related content, the query checker 25 may generate the content of the album from the metadata of the album (content = "MusicAlbum" & artist = "Sting") field. The query confirmation unit 25 infers that the user may be interested in accessing more albums of the same musician using this, and proposes (MusicAlbum, artist, "Sting") to the user as one of the search queries. .

When the user accesses content such as a broadcast TV program or a DVD, the query confirmation unit 25 uses caption data (closed captions) embedded in the stream to confirm the candidate search query. This embedded caption data contains information useful in forming the keyword. When the user wants to access related content while watching a TV program, the query confirmation unit 25 analyzes the caption text of the TV program to identify important keywords and proposes it to the user as a candidate search query.

The query confirmation unit 25 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. The 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 identifying keywords and suggesting them as candidate search keywords through the query confirmation unit 25 using natural language processing (NLP) to analyze the closed caption and confirm the keyword from the closed caption will be described later.

The closed caption (CC) of the TV program is embedded in the TV signal by the content provider before the broadcast is started. These are mainly for the deaf. Extracting useful information from this text is not simple. Captions generally do not contain any case information and exclude any attempt to extract the proper nouns based on the case information. Also, because of the colloquial nature of the content, they are often incompatible with grammar, run-off, and typos may exist. Due to this limitation, general keyword extraction techniques used in text documents may not be suitable for caption text. In addition, caption content is highly dependent on the type of program. The caption of the news program is high-content and realistic. Sitcom captions, on the other hand, are generally low on content and have a lot of slang. 4 illustrates a closed caption analyzer (CCA) 70 according to an embodiment of the present invention. 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 broadcast signals and processes a regular stream 74 of caption text entering the system. The CCA operates two history windows over the stream of incoming text (FIG. 5). The smaller 'most recent window' spans the last N sentences Si (N = 5 in this embodiment), while the larger 'program wide window' covers the entire TV program / Covers the current news story / current program section. Only keywords extracted from the 'program wide window' are stored and indexed for recommendation. Also, in order for the most recent keywords to appear at the top of the list of keywords displayed to the user, the keywords extracted from the 'most recent window' have a higher rank than others. As soon as the program or news story is changed, each window is initialized and restarted. The change is implied by special characters in the caption ('>>>' in the US) or determined by identifying the EPG and the current time.

CC tokenizer 78 receives stream 74 of CC text and splits it into sentences. This is done to preserve the grammar of the text. Next, a tagger 73 adds tags to the sentences. For example, add Brill's part of speech tag. (Brill 1992) Tagger 73 analyzes sentences to determine how each word is used in the sentence. Tagger 73 uses lexical rules to assign initial tags to each word in the sentence, and then uses contextual rules to update the tag based on the context in which the words are used. Contextual laws are sensitive to the grammar of the entered sentence. Incorrect or incomplete sentences can result in incorrect tagging of words in a sentence.

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

This means that in the previous sentence, "John" and "Wayne" are used as proper nouns, "ran" is a past tense and "home" is a noun.

The tagged sentence is passed from the tagger 73 to the rule engine 79. The law engine 79 extracts keywords from tagged sentences based on an extraction policy rule from a rule library 71. The Law Library (R) 71 identifies a set of laws that can be used to extract the various kinds of phrases present in a sentence. The law is expressed in tag patterns. For example, you may have a law (<PROP> +) for extracting consecutive proper nouns, and another law (<ADJ> + <NOUN> +) for extracting adverb consecutive to one or more nouns. May have Law selector 72 includes mapping genres to extraction policies. 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 requires the addition of identifying the types of keywords such as continuation of nouns, compound nouns, proper nouns, etc. To extract. On the other hand, if the program is a low-content and non-realistic program like sitcom, then a very conservative extraction policy is used that extracts keywords very selectively and only those keywords that are considered to be more practical, such as proper nouns. do. The law engine 79 changes the extraction behavior according to the type of the program being watched.

Each extraction policy Pe corresponds to a subset of the laws in R. The mapping can be set or obtained in advance. The mapping essentially defines the type of pattern that will be used to extract the keywords 76 from the program of a particular genre (type). In one example, the mapping is a small user study associated with four topics requested to indicate the keywords they wish to search from CC copies of four types of sample programs: news, sitcoms, talk shows, reality TV, etc. Can be determined by performing. The copy is tagged using Brill's tagger, and the tags of the displayed keywords are extracted according to the law. For example, if the keyword "Global Warming" is displayed in a news program, and the word is tagged with "Global <ADJ> Warming <NOUN>", then "<ADJ> <NOUN>" will contain the "news" genre. Is extracted according to the law. The highest ranked laws (based on frequency and thresholds) are used as the rules for forming extraction policies for that type of program, and the set of all laws for all types of programs form R. This facilitates the reusability of laws and extraction policies. The law engine 79 applies the extraction policy to the text received from the tagger 73 and extracts keywords from it. These keywords are then 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 of interest to the user. The query determining unit 27 extracts data related to candidate data identified as interested by the user, integrates the extracted data, and sets the correlation of the integrated data. Such correlation includes identifying associations between data. For example, data A is 'like' or 'same' as data B.

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

In addition, specific classes, called roulettes, are provided to perform the three tasks of data extraction, collection, or correlation establishment within the general query decision process. Roulettes include 'GetDataRuleLet', 'MergeDataRulet' and 'GetContentNotInHomeRuleLet'. 'GetDataRuleLet' acquires data from various data sources, 'MergeDataRulet' merges data obtained from various data sources, and 'GetContentNotInHomeRuleLet' extracts data / content that cannot be used in home devices (extracted from various sources). From a set of compiled data).

The planning phase essentially specifies the roulette to be executed and the set of input and output parameters required for the execution of the roulette. Specific fields within 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 expected from the execution of the roulette, and the range in which the output data is required (if applicable). The range field indicates whether the requested data should be available in the local or on the Internet. In order to satisfy various kinds of search queries, a plan library containing various kinds of plans is operated. When the user selects a search query, the query determining unit 27 plans based on the user's environment, such as whether the user is watching a TV program, watching a DVD or a music video, or listening to a music album. Check.

An example of using an execution plan on a search scenario combined with execution plans is described below. The search scenario relates to the case where a user is watching a documentary program broadcast entitled "Drumming Techniques" on TV. If the user is interested in accessing relevant Internet content, search assistant 24 identifies and displays candidate search queries from the closed caption of the program by executing the following planning steps. Acquire an EPG associated with the TV program the user is watching. A keyword is obtained from the EPG information obtained in the previous step. Check the genre of the TV program. Obtain 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 the 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>

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 drumming" and wants to see more related images that the user has not previously viewed. To resolve this request, the assistant 24 executes a plan including the following steps with "multiple rhythm drumming" set as a keyword. Obtain videos available on the Internet source (66 in FIG. 2) associated with the keyword "multiple rhythm drumming". Identify videos available in previously recorded homes related to "multiple rhythm drumming". Filter previously available videos from local source 69 in the resulting list after performing the previous step. An example of the 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>

Relevant internet videos that were not previously available in local source 69 are displayed to the user on the client module.

6 shows a functional block diagram 80 of an assistance system implemented with a context-specific search facilitator system (CSF) 82 in accordance with one embodiment of the present invention. The CSF 82 provides query confirmation functions such as keyword extraction and query determination functions such as data extraction, integration and correlation setup as described above. CSF 82 includes various layers to allow for constant search and access to CE device content and Internet content from data sources 81.

CSF 82 includes a data and query processing (DQP) layer 83. DQP 83 assists in determining user queries and also provides APIs for client applications to make use of it. Client applications 64 are shown outside of CSF 82, but may be included as components of CSF 82. The DQP 83 includes a query execution planner (QEP) 84 and an information source manager (ISM) 85. CSF 82 further includes a data exclusion (DE) layer 86. 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 searching and accessing relevant data available on the Internet and locally available data (ie, data stored on device 30 and / or device 20). QEP 84 operates a plan library 89 that includes a predetermined execution plan to be used to resolve data requests. QEP 84 manages roulette 90 classes that are executed as part of the plan. When QEP 84 receives a query from a client application, QEP 84 obtains the appropriate plan from plan library 89 and executes it. While the plan is being executed, the QEP 84 obtains the information / content requested by the user (via ISM 85) using the plug-ins 88 in the data extraction layer 86. ISM 85 maintains a directory containing detailed information about the type of data each data extraction plug-in component can extract and the type of input data predicted by plug-in 88 to do so. This allows QEP 84 to identify plug-ins 88 that provide a particular type of data.

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

DE 86 manages plug-ins 88, allows new plug-ins 88 to be inserted or removed with minimal code changes, and provides an application programming interface for higher layer components to use plug-ins. do.

As an example of a search assistance process by the CSF 82 according to the present invention, a TV viewer accessing the Internet is as follows. User Tricia is watching a TV program on "Druming Technology" through her TV, which is accomplished by video. She wants to know more about the topics covered in this program. In particular, we would like to know about the "multiple rhythm drumming" just mentioned. She presses the TV remote control 31 and searches for a host of information about the program he is watching. The UI graphic on the client module screen provides two menus. One menu 64A provides a list of keywords related to the TV program collected by the query confirmation unit of the CSF 82, with a highlight placed on the first keyword "multiple rhythm drumming." Another menu 64B shows a list of search results that include a web link including information and / or videos related to the keyword "multiple rhythm drumming." The search results are collected by the query deciding portion of the CSF 82. Trisha confirms that the second link on this menu is a "how to" video. Use the navigation buttons on the remote to move the highlight to this link and press the Select button to select and watch the video.

The scenario described above describes the following essential features. First, the user does not have to enter text or query terms at any point in time. The interaction is via a search button on a conventional remote control. Second, the user can access the relevant relevant 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 being watched, helps to search for the 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 the following.

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

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

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

4. Check the correlation of the information obtained in the above-mentioned steps.

5. Use correlations in forming queries to retrieve information from external sources such as regions or / and the Internet.

6. The search results show the user information related to the current user's activity (ie information that the user is interested in).

Confirming the correlation may be performed by one or more of the following methods.

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

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

(3) Identify the correlation between information related to the current user's activity and closely related information obtained from local and external sources.

In order to minimize the number of keys that the user must enter in order to receive information related to the user's current activity, the function supports mapping of information retrieval to several keys. For example, search maps to keys on the remote control. Then, specific information about the user's activity on the CE device is obtained. This involves acquiring metadata contained in media that can only be accessed by the CE device that renders the content. For example, the length and type of the content included in the CE or DVD.

The process may further include acquiring information embedded in a broadcast stream accessible only by the CE device that receives / renders. For example, subtitles and captions. In addition, information about content that already exists on the home network is obtained. For example, Sting's songs and metadata already owned by the user. In addition, information regarding appropriately structured data residing on the Internet is obtained. For example, metadata about a song already owned by a user is obtained from a compact disk database (CDDB). Additional relevant information is obtained from the partially semi-structured data present on the Internet. For example, a biography of the musician is obtained from an internet movie database (IMDB) and / or an appropriate web page. In addition, appropriate information is obtained from the unstructured information present on the Internet. For example, it is the address of a web page that conveys geographic, economic, political, and cultural information about the location from the main events reported in the news.

Collected / obtained information defines information at hand. Next, when the user operates the CE device, a correlation is established between the user's input to the CE device and ready-to-use information to automatically perform query formation to retrieve relevant information. This minimizes the need for a user to generate a query or minimizes the use of a keyboard to generate a query.

Next, from readily available information, a correlation is established between the data extracted from the Internet source and the data extracted from the home network content in order to refine the query for accurate search. A query plan is executed to retrieve a query on an external network such as the Internet or other resource without requiring user input. Query execution results are shown to the user in the form of search results. Preferably, the most appropriate information from the search results is selected to be presented to the user based on the information available immediately without requiring user input. Thus, the information to be shown to the user includes candidate information of interest to the user as it relates to information that is readily available.

Other examples of assisted search 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, user activity information and contextual information, and Obtaining closely related side information, obtaining correlations between side information, environmental information, and user activity information, and using the correlation 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 local network and / or external sources and obtaining additional information closely related to user activity information. Identifying the correlation may include verifying a correlation between information about the user's current activity and closely related information obtained from local sources. Identifying the correlation may include verifying a correlation between information about the user's current activity and closely related information obtained from external sources. Identifying the interrelationship may include verifying a correlation between information about the user's current activity and closely related information obtained from local and external sources.

Forming a query includes automatically forming a query without requesting input from the user. The query is run to obtain a search result that includes information related to the user's current activity. Executing the query includes executing the 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 the user interface in the device, such as the 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 an application 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.

Acquiring side information includes acquiring side information from external, unorganized data sources, acquiring information from external, semi-structured data sources, and from external broadcast data sources. May include obtaining information.

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

One of ordinary skill in the art to which the present invention pertains has the above-described program instructions executed by a processor, a program medium stored in a computer-readable medium, a computer on which a method is implemented, and a logic circuit. It can be appreciated that the present invention can be implemented in various ways such as an integrated circuit, firmware, or the like for describing an application. Although the present invention has been described within the scope of use with reference to the particular version preferred, other versions are possible. Accordingly, the scope and spirit of the appended claims should not be limited to the description of the preferred versions contained herein.

Meanwhile, the above-described embodiments of the present invention can be written as a program that can be executed in a computer, and can be implemented in a general-purpose digital computer that operates the program using a computer-readable recording medium.

The computer-readable recording medium may be a magnetic storage medium (for example, a ROM, a floppy disk, a hard disk, etc.), an optical reading medium (for example, a CD-ROM, a DVD, etc.) and a carrier wave (for example, the Internet). Storage medium).

So far I looked at the center of the preferred embodiment for the present invention. Those skilled in the art will appreciate that the present invention can be implemented in a modified form without departing from the essential features of the present invention. Therefore, the disclosed embodiments should be considered in descriptive sense only and not for purposes of limitation. The scope of the present invention is shown in the claims rather than the foregoing description, and all differences within the scope will be construed as being included in the present invention.

By automatically forming a query without a user's request for input, it allows a user of CE devices to have improved access to the Internet.

1 illustrates a network implementing a method for facilitating information retrieval by a user according to an embodiment of the present invention.

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

3 shows a flowchart of the overall steps involved in a method for facilitating information retrieval according to the present invention.

4 illustrates an embodiment of keyword selection according to the present invention.

5 illustrates an embodiment of torqueizing according to the present invention.

6 illustrates an embodiment of a structure that facilitates searching using an execution plan in accordance with the present invention.

One embodiment of the present invention, the method comprising the steps of obtaining information about user interests; Identifying candidate data of interest to the user; Extracting data related to the data of interest to the user; And collecting the relevant data extracted for presentation to the user on the device.

Identifying candidate data of interest to the user includes: monitoring user access to content; Selecting a set of extraction laws for extracting information; And extracting key information from metadata regarding the content based on the selected extraction rule.

Selecting the set of extraction laws may further include selecting a set of extraction laws based on the type of content.

Selecting the set of extraction laws further includes selecting a set of extraction laws from a rule library based on the content type, wherein the law library is a list of rules for extracting various keywords. It may include.

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

Obtaining information about the user's interests may further include obtaining contextual information about the current activity of the user on a local network.

The method may further include establishing a correlation of the related data to be displayed to the user.

Extracting data related to the data of interest to the user may include forming a query to search the related data based on candidates of the data of interest.

The method may further include 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.

Executing the query may include searching the Internet for the related data.

Another aspect of the invention is an information collection unit configured to identify information about user interests; A verification unit configured to identify candidate data of interest to the user; An extraction unit configured to extract data related to the data of interest to the user; And a collecting unit configured to collect the extracted related data for showing to the user on the device.

Claims (25)

A method for allowing a user of a CE device to easily retrieve information, Obtaining information regarding user interests; Identifying candidate data of interest to the user; Extracting data related to the data of interest to the user; And Collecting the extracted related data for presentation to the user on the device. The method of claim 1, wherein identifying candidate data of interest to the user comprises: Monitoring user access to the content; Selecting a set of extraction laws for extracting information; And Extracting key information from metadata regarding the content based on the selected extraction rule. The method of claim 2, wherein the selecting of the set of extraction laws comprises: Selecting a set of extraction laws based on the type of content. 4. The method of claim 3, wherein selecting a set of extraction laws comprises: Selecting a set of extraction rules from a rule library based on the content type, And the law library comprises a list of rules for extracting various keywords. The method of claim 1, wherein the obtaining of the information about the interest of the user comprises: Acquiring information about the current activity of the user on the device. The method of claim 5, wherein the obtaining of the information about the interest of the user comprises: Obtaining contextual information about the current activity of the user on a local network. The method of claim 1, Establishing a correlation of said related data to be displayed to said user. The method of claim 1, wherein extracting data related to the data of interest to the user comprises: Forming a query for searching the related data based on candidates of the data of interest. The method of claim 8, Executing a query to retrieve relevant information from at least one of the local network and an external source. The method of claim 9, wherein the device, And a CE device. The method of claim 10, wherein executing the query comprises: Searching the Internet for the related data. A device for allowing a user of a CE device to easily retrieve information, An information collector configured to identify information about user interests; A verification unit configured to identify candidate data of interest to the user; An extraction unit configured to extract data related to the data of interest to the user; And And a collecting unit configured to collect the extracted related data for showing to the user on the device. The method of claim 12, wherein the identification unit, Monitoring user access to content, selecting a set of extraction laws for information extraction, and extracting key information from metadata about the content based on the selected extraction law to obtain candidate data of interest to the user; And further configured to check. The method of claim 13, wherein the identification unit, And select a set of extraction rules based on the content type. The method of claim 14, wherein the identification unit, Select a set of extraction rules from a law library based on the content type, And the rule library includes a list of rules for extracting various keywords. The method of claim 12, wherein the information acquisition unit, And obtain information about the user interest by obtaining information about the user's current activity on the device. The method of claim 16, wherein the information acquisition unit, And obtain information about user interests by obtaining contextual information about a user's current activity on the local network. The method of claim 12, wherein the collecting unit, And to correlate the related data to be displayed to the user. The method of claim 12, wherein the extraction unit, And form a query to retrieve the related data based on candidates of the data of interest. The method of claim 19, wherein the extraction unit, And execute a query to retrieve relevant information from the local network and / or external source. The method of claim 20, wherein the device, A device comprising a CE device. The method of claim 21, wherein the extraction unit, And further search the Internet for the related data. In a system that allows a user to easily retrieve information, An electronic device for access to content; And Including facilitator, The assistant, An information collector configured to identify information about the user interests; A verification unit configured to identify candidate data of interest to the user; An extraction unit configured to extract data related to the data of interest to the user; And And a collector configured to collect relevant data extracted for presentation to the user on the device. A computer-readable recording medium having recorded thereon a program for executing the method of claim 1. A computer-implemented method for allowing a user of a CE device to easily retrieve information, Obtaining information regarding user interests; Identifying candidate data of interest to the user; Extracting data related to the data of interest to the user; And Collecting the extracted related data for presentation to the user on the device.

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