TY - GEN
T1 - Query reuse based query planning for searches over the deep web
AU - Wang, Fan
AU - Agrawal, Gagan
PY - 2010
Y1 - 2010
N2 - Nowadays, data dissemination often involves online databases that are hidden behind query forms, thus forming the deep web. Lately, there has been a lot of research interest on supporting query answering over the deep web. To answer a deep web query efficiently, the current approaches generate a query plan for each query independently. However, in practice, deep web queries issued by a user over a short period of time can often share similarities. This, if properly utilized, can help us in generating more efficient query plan. In this paper, we have developed a solution for generating query plan for a deep web query based on the similarities between a given query and a set of earlier queries. Our algorithm systematically finds the reusable components of earlier query plans, and then develops a new query plan reusing these. While the resulting query plans may not be optimal, they are likely to enable more data reuse, and hence, speedup the execution.
AB - Nowadays, data dissemination often involves online databases that are hidden behind query forms, thus forming the deep web. Lately, there has been a lot of research interest on supporting query answering over the deep web. To answer a deep web query efficiently, the current approaches generate a query plan for each query independently. However, in practice, deep web queries issued by a user over a short period of time can often share similarities. This, if properly utilized, can help us in generating more efficient query plan. In this paper, we have developed a solution for generating query plan for a deep web query based on the similarities between a given query and a set of earlier queries. Our algorithm systematically finds the reusable components of earlier query plans, and then develops a new query plan reusing these. While the resulting query plans may not be optimal, they are likely to enable more data reuse, and hence, speedup the execution.
UR - http://www.scopus.com/inward/record.url?scp=78049353874&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=78049353874&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-15251-1_5
DO - 10.1007/978-3-642-15251-1_5
M3 - Conference contribution
AN - SCOPUS:78049353874
SN - 3642152503
SN - 9783642152504
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 64
EP - 79
BT - Database and Expert Systems Applications - 21st International Conference, DEXA 2010, Proceedings
T2 - 21st International Conference on Database and Expert Systems Applications, DEXA 2010
Y2 - 30 August 2010 through 3 September 2010
ER -