Patent Application
20080172364
Program applications, such as browsers include methods and functions to browse or edit documents, such as web pages retrieved from the World Wide Web (“web”). Often times a user may want to retrieve additional information or documents related to a particular subject or topic in the document that the user is browsing. To retrieve additional information pertaining to a particular subject, the user may invoke a new browser frame or application to search for supplemental documents or information for the particular topic or subject area of interest.
The user then enters a search query to retrieve documents related to the particular subject of interest. Typical search engines retrieve documents that contain all of the search query terms; thus, when a query contains many terms, relevant documents may be missed because they do not contain one of the queried terms (instead, they may contain a synonym or a different inflection of the term). Because of this and also because of the effort involved in typing, users tend to write very short queries (i.e. containing very few terms). Unfortunately, such queries do not include sufficient context details and tend to be highly ambiguous. Consequently, many irrelevant documents are retrieved. For example, while reading an article about the Space station repairs, a user may attempt to find out more about the heat shield mentioned in the article by sending the query “heat shield” to a web search engine. Because the query is ambiguous, it may happen that none of the top results for this two-word is relevant to the user's informational need in the current context, as these results discuss roofing and house thermal insulation.
After refining the query or examining many search results, the user may find a relevant document. On one hand, if the user does not bookmark the document, it is difficult for the user to remember the source of the document should the user desire to review the document again in relation to the particular subject area or topic. On the other hand, users do not want to create very many bookmarks because this would make the process of finding any particular bookmark very difficult.
The discussion above is merely provided for general background information and is not intended to be used as an aid in determining the scope of the claimed subject matter.
The application relates to a context based search and document retrieval application which invokes a document analysis component to generate context data for a document such as a web page. The context data is provided to a search query generator, which is configured to generate a contextually annotated search query based on a user query and the context of the original document examined by the user. In embodiments described, the application also enables contextual bookmarking of one or more of the documents retrieved in response to the contextually annotated search query. The application then provides access to the bookmarked documents for other documents with similar contexts to the context of the original document and can automatically hyperlink them to terms in these other documents.
This Summary is provided to introduce a selection of concepts in a simplified form that are further described below in the Detailed Description. This Summary is not intended to identify key features or essential features of the claimed subject matter, nor is it intended to be used as an aid in determining the scope of the claimed subject matter. The claimed subject matter is not limited to implementations that solve any or all disadvantages noted in the background.
With reference to
Computer 110 typically includes a variety of computer readable media. Computer readable media can be any available media that can be accessed by computer 110 and includes both volatile and nonvolatile media, removable and non-removable media. By way of example, and not limitation, computer readable media may comprise computer storage media and communication media. Computer storage media includes both volatile and nonvolatile, removable and non-removable media implemented in any method or technology for storage of information such as computer readable instructions, data structures, program modules or other data. Computer storage media includes, but is not limited to, RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, digital versatile disks (DVD) or other optical disk storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other medium which can be used to store the desired information and which can be accessed by computer 110. Communication media typically embodies computer readable instructions, data structures, program modules or other data in a modulated data signal such as a carrier wave or other transport mechanism and includes any information delivery media. The term “modulated data signal” means a signal that has one or more of its characteristics set or changed in such a manner as to encode information in the signal. By way of example, and not limitation, communication media includes wired media such as a wired network or direct-wired connection, and wireless media such as acoustic, RF, infrared and other wireless media. Combinations of any of the above should also be included within the scope of computer readable media.
The system memory 130 includes computer storage media in the form of volatile and/or nonvolatile memory such as read only memory (ROM) 131 and random access memory (RAM) 132. A basic input/output system 133 (BIOS), containing the basic routines that help to transfer information between elements within computer 110, such as during start-up, is typically stored in ROM 131. RAM 132 typically contains data and/or program modules that are immediately accessible to and/or presently being operated on by processing unit 120. By way of example, and not limitation,
The computer 110 may also include other removable/non-removable volatile/nonvolatile computer storage media. By way of example only,
The drives and their associated computer storage media discussed above and illustrated in
A user may enter commands and information into the computer 110 through input devices such as a keyboard 162, a microphone 163, and a pointing device 161, such as a mouse, trackball or touch pad. Other input devices (not shown) may include a joystick, game pad, satellite dish, scanner, or the like. These and other input devices are often connected to the processing unit 120 through a user input interface 160 that is coupled to the system bus, but may be connected by other interface and bus structures, such as a parallel port, game port or a universal serial bus (USB). A monitor 191 or other type of display device is also connected to the system bus 121 via an interface, such as a video interface 190. In addition to the monitor, computers may also include other peripheral output devices such as speakers 197 and printer 196, which may be connected through an output peripheral interface 195.
The computer 110 is operated in a networked environment using logical connections to one or more remote computers, such as a remote computer 180. The remote computer 180 may be a personal computer, a hand-held device, a server, a router, a network PC, a peer device or other common network node, and typically includes many or all of the elements described above relative to the computer 110. The logical connections depicted in
When used in a LAN networking environment, the computer 110 is connected to the LAN 171 through a network interface or adapter 170. When used in a WAN networking environment, the computer 110 typically includes a modem 172 or other means for establishing communications over the WAN 173, such as the Internet. The modem 172, which may be internal or external, may be connected to the system bus 121 via the user input interface 160, or other appropriate mechanism. In a networked environment, program modules depicted relative to the computer 110, or portions thereof, may be stored in the remote memory storage device. By way of example, and not limitation,
As shown, the second application component 210 invokes a context search query generator 214 which receives input context data 206, including document context data, generated by the document analysis component 204 and a user's input search query 216. The context search query generator 214 uses the context data 206 and the input search query 216 to generate a contextually annotated search query 218 to retrieve additional documents or information based upon the context of the original document. The contextually annotated search query 218 includes additional search terms to focus a search based upon the context of the original document.
As previously described, the document context data is used to retrieve related documents through the second application component 210. Related documents similarly can be any of a web page, text document stored locally or a text document stored on another accessible computer. As shown in
The search query generator 214 is invoked through a user interface 250 as illustrated in
As shown in the illustrated embodiment, the search results for the contextually annotated search query 218 are displayed in the second display panel 254 as illustrated in
Upon review of the search results, a user can select a particular document for viewing in the display panel 254 as shown in
Upon activation of the bookmark function, a bookmark component 266 is invoked to create a bookmark having an associated context 270. The associated context is based upon the context of the original document. As shown, the bookmark component 266 uses the input search query 216 and the context data 206 to generate the bookmark 270 for document 265. The bookmark 270 includes a document link or address for the retrieved document 265, the user search query (or the selected string from the original document), and the associated context data. If the search query appears in the original document then a hyperlink 274 is created for the bookmark document for the instances of the search query in the original document.
In an illustrated example, the user reads a document about the war in Iraq, which contains the word tactics. The user selects to retrieve additional documents or information for the term <tactics> in the original document. In response to the selection, the application creates a contextually annotated query (e.g.: “tactics+prefer:iraq+prefer:war+prefer:insurgency+prefer:us+prefer:army”) and retrieves one or more documents based upon this search query. The application retrieves the top N results (for example, N=200) from the search engine, re-ranks them based on their match with the context of the original document, and presents the new sorted list of results to the user. The user can then select to create a bookmark for one or more of the retrieved documents. Upon activation of the bookmark selection, the bookmark component 266 creates the contextual bookmark 270 including a link to the selected document, the search term <tactics>, and the associated context. The bookmark can then be used to create hyperlinks in the original document or later, in other documents with similar contexts to the context of the original document, from the term <tactics> to the bookmarked document.
As previously described, a document is processed by the document analysis component 204 to generate context data.
As shown, the document analysis component 204 includes an extraction/disambiguation component 320 and a context component 322. The extraction/disambiguation component 320 extracts entities and terms from the document and disambiguates the extracted terms and entities. For example, the component 300 uses information from query logs 310 and context libraries to disambiguate entities. The context component 322 generates context data 206 for the extracted terms or entities in the document as well as document context data generated based upon important terms and entities extracted from the document. The context data is used to retrieve documents and information related to the context of the document as previously described.
In the embodiment illustrated in
Popular terms are extracted based upon query logs or other context data collections. The importance of a term in a document can be estimated in various ways. In one embodiment, the application estimates the term importance as follows:
The document set used for determining IDF can be specific to the type of document analyzed. For example, if the document is an article from MSNBC®, the collection can be a large set of MSNBC® articles. Alternatively, the document set used in the IDF computation can be based upon a local collection of documents on the user's computer. For example, in one embodiment, the Desktop search index on the user's computer is used to compute IDF data from term occurrence statistics in a collection of browsed documents.
The document analysis component 204 also extracts bookmark terms from bookmarked data 314 stored locally and/or on the web server 304. The bookmark data 314 can be used to create context hyperlinks. In particular, the bookmark data 314 is used to create hyperlinks in a document for terms in a document with a context similar to the associated context of the bookmark. For example, in an illustrated embodiment, the document analysis component 204 generates a hyperlink for a bookmarked term present in the input document to the bookmarked document or documents associated with that term if the context of the bookmark and the input document are sufficiently similar. This is equivalent to saying that the context of the original document in which the bookmark was created and the context of the input document are sufficiently similar.
Although the subject matter has been described in language specific to structural features and/or methodological acts, it is to be understood that the subject matter defined in the appended claims is not necessarily limited to the specific features or acts described above. Rather, the specific features and acts described above are disclosed as example forms of implementing the claims.
