Paper: Combining Multiple Forms Of Evidence While Filtering

ACL ID H05-1074
Title Combining Multiple Forms Of Evidence While Filtering
Venue Conference on Empirical Methods in Natural Language Processing
Session Main Conference
Year 2005
Authors

This paper studies how to go beyond relevance and enable a filtering system to learn more in- teresting and detailed data driven user models from multiple forms of evidence. We carry out a user study using a real time web based per- sonal news filtering system, and collect exten- sive multiple forms of evidence, including ex- plicit and implicit user feedback. We explore the graphical modeling approach to combine these forms of evidence. To test whether the ap- proach can help us understand the domain bet- ter, we use graph structure learning algorithm to derive the causal relationships between dif- ferent forms of evidence. To test whether the approach can help the system improve the per- formance, we use the graphical inference algo- rithms to predict whether a user likes a docu- ment ba...