A. Eckhardt
P. Vojtas
ABSTRACT
Web search heuristics based on Fagin's threshold algorithm assume we have the user profile in the form of particular attribute ordering and a fuzzy aggregation function representing the user combining function. Having these, there are sufficient algorithms for searching top-k answers. Finding particular attribute ordering and aggregation for a user still remains a problem. In this short paper our main contribution is a proof of concept of a new iterative process of acquisition of user preferences and attribute ordering .
Index Terms
- PHASES: A User Profile Learning Approach for Web Search
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