Optimized Query Execution in Large Search Engines

Abstract Large web search engines have to answer,thousands of queries per second with interactive response times. A major factor in the cost of executing a query is given by the lengths of the inverted lists for the query terms, which increase with the size of the document,collection and are often in the range of many megabytes. To address this issue, IR and database researchers have proposed pruning techniques that compute or approximate term-based ranking functions without scanning over the full inverted lists. Over the last few years, search engines have in-