document: Query-driven indexing for peer-to-peer text retrieval We describe a query-driven indexing framework for scalable text retrieval over structured P2P networks . To cope with the bandwidth consumption problem that has been identified as the major obstacle for full-text retrieval in P2P networks , we truncate posting lists associated with indexing features to a constant size storing only top-k ranked document references . To compensate for the loss of information caused by the truncation , we extend the set of indexing features with carefully chosen term sets . Indexing term sets are selected based on the query statistics extracted from query logs , thus we index only such combinations that are a ) frequently present in user queries and b ) non-redundant w.r.t the rest of the index . The distributed index is compact and efficient as it constantly evolves adapting to the current query popularity distribution . Moreover , it is possible to control the tradeoff between the storage\/bandwidth requirements and the quality of query answering by tuning the indexing parameters . Our theoretical analysis and experimental results indicate that we can indeed achieve scalable P2P text retrieval for very large document collections and deliver good retrieval performance .
doc_bio_tags: O O O O B I O O O O O O O O B I O O B O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B B I O O O O O O O O O O O