Learning Subjective Relevance to Facilitate Information Access

As the amount of available electronic information is dramatically increasing, the ability for rapid and e ective access to information has become critical. Most traditional information access methods rely on measures of relevance based on information content. We propose a new approach which augments existing information access methods with subjective relevance learned from user feedback. We developed an adaptive system which helps users access information by employing learned knowledge about which documents are likely to be relevant, given the current user's information need and user pro le. This system is based on a model, called a relevance network, which learns and generalizes relevance information in a rapid, cost-e ective, and incremental manner. We present the design of the relevance network and results of experimental evaluation.

• Type: Conference
• Year: 1995
• Where: CIKM
• Authors: James R. Chen, Nathalie Mathe
• Keywords: CIKM 1995, Information Access Methods, Information Management, Relevance Network, Subjective Relevance