Faceted Federated Search
In searching for documents, traditional federated search engines emphasize the use of standard query parameters, such as author, title, and date range. Although most sources provide for a full-record search, users are left to guess at which terms might yield results. It would be much more useful if the search engine could provide a useful view of the search terms that actually occur in the documents and provide guidance to enable users to select and refine their queries. However, because the sources can not be exhaustively queried or preprocessed, it is not possible, in the general case, to provide a useful view of the search terms that occur in sources. This project will develop technology that will quickly focus the user on a small subset of documents that can be analyzed interactively. Users then will be able to ¿navigate¿ over actual terms, rather than guessing. Commercial Applications and other Benefits as described by the awardee: The enhanced search capability should vastly improve the effectiveness of large scale distributed searches, accelerate the research process, and improve the quality and timeliness of research results. More timely research would accelerate the scientific process and have a direct impact on government and commercial R&D departments in large scientific and technical enterprises.
Small Business Information at Submission:
Deep Web Technologies, Llc
301 North Guadalupe Suite 201 Santa Fe, NM 87501
Number of Employees: