ReDRIVE: result-driven database exploration through recommendations

Typically, users interact with database systems by formulating queries. However, many times users do not have a clear understanding of their information needs or the exact content of the database, thus, their queries are of an exploratory nature. In this paper, we propose assisting users in database exploration by recommending to them additional items that are highly related with the items in the result of their original query. Such items are computed based on the most interesting sets of attribute values (or faSets) that appear in the result of the original user query. The interestingness of a faSet is defined based on its frequency both in the query result and in the database instance. Database frequency estimations rely on a novel approach that employs an ǫ-tolerance closed rare faSets representation. We report evaluation results of the efficiency and effectiveness of our approach on both real and synthetic datasets. Categories and Subject Descriptors H.3.3 [Information Storage ...

• Type: Journal
• Year: 2011
• Where: CIKM
• Authors: Marina Drosou, Evaggelia Pitoura
• Keywords: CIKM 2011, Database Exploration, Database Frequency, Information Storage And Retrieval, Information Technology