A Novel Framework to Measure the Degree of Difficulty on Keyword Query Routing

Abstract

Spatial queries, such as range search and nearest neighbor retrieval, involve only conditions on objects geometric properties. A spatial database manages multidimensional objects(such as points, rectangles, etc.), and provides fast access to those objects based on different selection criteria.Keyword queries on databases provide easy access to data, but often suffer from low ranking quality, i.e., low precision and/or recall, as shown in recent benchmarks. It would be useful to identify queries that are likely to have low ranking quality to improve the user satisfaction. For instance, the system may suggest to the user alternative queries for such hard queries. In this paper, we analyze the characteristics of hard queries and propose a novel framework to measure the degree of difficulty for a keyword query over a database, considering both the structure and the content of the database and the query results. We evaluate our query difficulty prediction model against two effectiveness benchmarks for popular keyword search ranking methods. we present a suite of optimizations to minimize the incurred time overhead.