A Controlled Knowledge Base Evolution Approach for Query Hits Merging in P2P Systems
Merging query-hits in large scale systems, like P2P, is challenging and potentially complex because results have to be ranked with respect to each other while sources are heterogeneous and with no centralized control. To solve this problem, the authors advocated in a knowledge-based approach relying on users profiles. A user profile includes information about past interests derived from the user past actions as well as information about peers from which results were obtained in the past for similar queries. Using a knowledge base can lead to the system obsolescence unless an effective approach is proposed to evolve this learned knowledge. Most used approaches for knowledge update are periodic and cannot react on user needs changes at the appropriate time.