Profiling with the INFOrmer Text Filtering Agent

Humphrey Sorensen (Department of Computer Science, University College Cork, Ireland)

Adrian O'Riordan (Department of Computer Science, University College Cork, Ireland)

Colm O'Riordan (Department of Computer Science, University College Cork, Ireland)

Abstract: INFOrmer is an intelligent filtering system, currently being applied to the management of USENET News articles. An individual may have one or more profiles, each representing a long-term interest of that user. The user profile is then used to measure the relevance of incoming articles and filter out irrelevant documents. A user profile may be modified as a result of relevance feedback, so that it adjusts to users changing interests. This paper discusses the architecture of INFOrmer and covers the profile/document representation and comparison techniques adopted within the system.

Keywords: Text filtering, relevance feedback., semantic network, spreading activation

Categories: H.3.3