Practical Relevance Ranking for 10 Million Books.

Abstract. In this paper we briefly describe our production environment and some of the open questions about relevance ranking for 10 million books. Then we describe our participation in the Prove It task of the INEX Social Book Search Track. We found that the queries supplied with the Prove It topics were not specific enough to provide good retrieval results. In contrast, the fact fields of the topics, when used as queries, provided good retrieval results. However, our query logs show that users are unlikely to enter queries as long as the fact fields. We tried to create queries that provided good retrieval results but better represented the queries in our logs. We also experimented with simulating the two-stage search process used in our production system when searching the en-tire corpus of 10 million books to find relevant books and then searching within the book to find relevant pages. While we succeeded in creating queries that were more specific than those supplied in the Prove It topics, and those queries produced better results, questions remain about how representative these created queries are of real user queries.