Profiling with the INFOrmer Text Filtering Agent

Humphrey Sorensen; Adrian Riordan; Colm Riordan

doi:10.3217/jucs-003-08-0988

JUCS - Journal of Universal Computer Science 3(8): 988-1006, doi: 10.3217/jucs-003-08-0988

Profiling with the INFOrmer Text Filtering Agent

Humphrey Sorensen^‡, Adrian O Riordan^‡, Colm O Riordan^‡

‡ Department of Computer Science, University College Cork, Ireland

Corresponding author: Humphrey Sorensen ( h.sorensen@cs.ucc.ie )

This article is freely available under the J.UCS Open Content License.

Citation: Sorensen H, Riordan AO, Riordan CO (1997) Profiling with the INFOrmer Text Filtering Agent. JUCS - Journal of Universal Computer Science 3(8): 988-1006. https://doi.org/10.3217/jucs-003-08-0988

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, semantic network, spreading activation, relevance feedback.