Title :
Using element and document profile for information clustering
Author :
Lai, Jun ; Soh, Ben
Author_Institution :
Dept. of Comput. Sci. & Comput. Eng., La Trobe Univ., Australia
Abstract :
The tremendous growth in the amount of information available and the number of visitors to Web sites in the recent years poses some key challenges for information filtering and retrieval. Web visitors not only expect high quality and relevant information, but also wish that the information be presented in an as efficient way as possible. The traditional filtering methods, however, only consider the relevant values of document. These conventional methods fail to consider the efficiency of documents retrieval. In this paper, we propose a new algorithm to calculate an index called document similarity score based on elements of the document. Using the index, document profile will be derived. Any documents with the similarity score above a given threshold are clustered. Using these pre-clustered documents, information filtering and retrieval can be made more efficient.
Keywords :
Web sites; document handling; information filters; information retrieval; pattern clustering; search engines; Web sites; Web visitors; document profile; document retrieval; document similarity score; information clustering; information filtering; information retrieval; search engine; Books; Clustering algorithms; Computer science; Conference proceedings; Information filtering; Information filters; Information retrieval; Internet; Search engines; Web sites;
Conference_Titel :
e-Technology, e-Commerce and e-Service, 2004. EEE '04. 2004 IEEE International Conference on
Print_ISBN :
0-7695-2073-1
DOI :
10.1109/EEE.2004.1287354