Title :
SmartPortal for Biomedical Data Mining
Author :
Buczak, Anna L. ; Wan, Charles ; Petry, Glenn
Author_Institution :
Sarnoff Corp., Princeton, NJ
fDate :
March 1 2007-April 5 2007
Abstract :
Efficient data retrieval from large databases and the World Wide Web is an important task that has to be performed routinely in a wide range of applications. To facilitate the drug discovery process, the biomedical community needs tools that enable fast searching of databases and the Web. SmartPortal assists users in their searches of biomedical information by quickly finding results of particular interest to the user in the deluge of data and the moving them to the top of the results list. SmartPortal achieves its goal through 1) constructing a user model for each particular user that captures the type of information of interest to that user; 2) using machine learning technologies to adapt the model to changing user needs, and to learn from user feedback what type of information is of interest to the user at any given moment; 3) automatic query expansion (using ontologies) to help the user construct useful queries faster and retrieve pertinent information
Keywords :
learning (artificial intelligence); medical information systems; ontologies (artificial intelligence); portals; query formulation; query processing; relevance feedback; SmartPortal; World Wide Web; automatic query expansion; biomedical community; biomedical data mining; biomedical information; data retrieval; database searching; drug discovery process; information queries; information retrieval; large databases; machine learning; ontologies; user feedback; Bioinformatics; Data mining; Databases; Drugs; Feedback; Filtering; Humans; Information retrieval; Lenses; Web sites;
Conference_Titel :
Computational Intelligence and Data Mining, 2007. CIDM 2007. IEEE Symposium on
Conference_Location :
Honolulu, HI
Print_ISBN :
1-4244-0705-2
DOI :
10.1109/CIDM.2007.368876