USTB at Social Book Search 2015 Suggestion Task: Metadata Expansion and Reranking.

In this paper, we describe our participation in the INEX 2015 Social Book Search(SBS) Track Suggestion Task. We try out all possible groups of XML elds to nd out the most eective group for relevance feedback model. We investigate the contribution of user-generated data and construct a social book search system based on several important techniques. Focus on the lack of important information of the majority books, we use document expansion by crawling book information from other two web sites which can enrich the index. And then we perfor- m re-ranking on Galago searching results on enriched XML index by 11 dierent strategies and combine the results with learning to rank. Experiments on these methods show that an enriched index and query model improves the eectiveness. As our methods in INEX 2014 (1), re- ranking and Random Forests combining those re-ranking models show better performance.