초록 ▼

An information highlighting facility assists the user in evaluating relevance of accessed documents to the user's information need. The accessed documents may, for example, be identified by a search engine in response to a user query. When accessing documents identified as relevant by a search engin

An information highlighting facility assists the user in evaluating relevance of accessed documents to the user's information need. The accessed documents may, for example, be identified by a search engine in response to a user query. When accessing documents identified as relevant by a search engine from other networked computers, the facility provides information highlighting to assist the user in determining whether the document is relevant. A model of the user's interest, which may include an augmented set of search terms, is used to take into account the general interest of the user as captured by an interest profile and context of use of the computer by the user, or a combination thereof. The model of the user's interest is applied to the document text as the document is accessed from its source. The highlighting of information about the document content may include highlighting of the terminology in the text, scrolling of the document to the relevant passages, identification of entity names and entity relations, creation of a document summary and a document thumbnail, etc. In addition, the model can be applied to a set of documents accessed by the user, e.g., to re-rank the top scoring documents from the result set provided to the user by a search engine or some other information providing services.

대표청구항 ▼

What is claimed is: 1. A computer implemented method of enhancing query results provided independent of a search engine, the method comprising: sending a query to an independent search engine; create a context based at least in part upon a user model; receiving query results from the search engine;

What is claimed is: 1. A computer implemented method of enhancing query results provided independent of a search engine, the method comprising: sending a query to an independent search engine; create a context based at least in part upon a user model; receiving query results from the search engine; retrieving at least one document identifying by the query results; displaying the at least one document; identifying at least one name of a person or a company within the at least one document; generating a list of the at least one name of a person or company in a separate window from the at least one document, wherein each name is provide with features to navigate to occurrences of the name in the at least one document; dividing the document into sections, and generating a relevancy score for each section based upon the context; and automatically scrolling to a section of the document with a highest relevancy score. 2. The method of claim 1, each section is one of a paragraph, a sentence, and a predetermined number of lines of text. 3. The method of claim 1, wherein the at least one name includes a name of at least one person and a name of at least one company. 4. The method of claim 3, identifying a relationship between the at least one person and the at least one company. 5. The method of claim 4, providing links to pages including the name of the at least one person and the name of the at least one company mentioned in the identified relationship. 6. A system embodied on a computer readable storage medium for enhancing query results provided independent of a search engine, the system comprising: a module that sends a query to a search engine separate from the computer; a module that receives query results from the search engine; a module that retrieves documents identified by the query results; a module that enhances the query based at least in part upon a user model; a module that applies the enhanced query to the retrieved documents; and a module that generated information regarding relevancy of the retrieved documents based at least in part upon the enhanced query and the user model, wherein a name of a person and name of a company are identified with the retrieved documents and a relationship between the person and company is identified, the module that generates information regarding relevancy provides links to retrieved documents that contain the name of the person and the name of the company mentioned in the identified relationship. 7. The system of claim 6, the query is enhanced based on at least one of linguistic analysis, a general interest profile, a model of user interest generated independent of search result. 8. The method of claim 7, the linguistic analysis comprises at least one of syntactic and semantic analysis. 9. The system of claim 6, further containing a module that re-ranks the query results based on information contained in the retrieved documents and upon the user model. 10. The system of claim 6, further containing a module that automatically scrolls to a most relevant portion of a retrieved document based at least in part upon the user model.