Exploiting web search engines to search structured databases Export

@inproceedings{citeulike:4400905, abstract = {Web search engines often federate many user queries to relevant structured databases. For example, a product related query might be federated to a product database containing their descriptions and specifications. The relevant structured data items are then returned to the user along with web search results. However, each structured database is searched in isolation. Hence, the search often produces empty or incomplete results as the database may not contain the required information to answer the query. In this paper, we propose a novel integrated search architecture. We establish and exploit the relationships between web search results and the items in structured databases to identify the relevant structured data items for a much wider range of queries.Our architecture leverages existing search engine components to implement this functionality at very low overhead. We demonstrate the quality and efficiency of our techniques through an extensive experimental study.}, address = {New York, NY, USA}, author = {Agrawal, Sanjay and Chakrabarti, Kaushik and Chaudhuri, Surajit and Ganti, Venkatesh and Konig, Arnd C. and Xin, Dong}, booktitle = {WWW '09: Proceedings of the 18th international conference on World wide web}, citeulike-article-id = {4400905}, citeulike-linkout-0 = {http://portal.acm.org/citation.cfm?id=1526709.1526777}, citeulike-linkout-1 = {http://dx.doi.org/10.1145/1526709.1526777}, comment = {[Talk] Structured information is interesting for users, as many queries are about entities; however sometimes the info in the database is not enough for a free text query. Complement database search using web info from web pages. Identify and aggregate entities that are in close proximity of ocurrences of a query on web pages. These pages are the same ones returned by the search engine for the query, so there is no extra call to the web search backend. Scoring: aggregates using factors such as proximity or document importance.}, doi = {10.1145/1526709.1526777}, isbn = {978-1-60558-487-4}, keywords = {databases, search, similarity, text}, location = {Madrid, Spain}, pages = {501--510}, posted-at = {2009-04-24 16:30:43}, priority = {0}, publisher = {ACM}, title = {Exploiting web search engines to search structured databases}, url = {http://dx.doi.org/10.1145/1526709.1526777}, year = {2009} }

TY - CONF ID - citeulike:4400905 L3 - citeulike-article-id:4400905 N2 - Web search engines often federate many user queries to relevant structured databases. For example, a product related query might be federated to a product database containing their descriptions and specifications. The relevant structured data items are then returned to the user along with web search results. However, each structured database is searched in isolation. Hence, the search often produces empty or incomplete results as the database may not contain the required information to answer the query. In this paper, we propose a novel integrated search architecture. We establish and exploit the relationships between web search results and the items in structured databases to identify the relevant structured data items for a much wider range of queries.Our architecture leverages existing search engine components to implement this functionality at very low overhead. We demonstrate the quality and efficiency of our techniques through an extensive experimental study. CY - Madrid, Spain SN - 978-1-60558-487-4 AD - New York, NY, USA EP - 510 TI - Exploiting web search engines to search structured databases PB - ACM T2 - WWW '09: Proceedings of the 18th international conference on World wide web SP - 501 KW - databases KW - search KW - similarity KW - text N1 - [Talk] Structured information is interesting for users, as many queries are about entities; however sometimes the info in the database is not enough for a free text query. Complement database search using web info from web pages. Identify and aggregate entities that are in close proximity of ocurrences of a query on web pages. These pages are the same ones returned by the search engine for the query, so there is no extra call to the web search backend. Scoring: aggregates using factors such as proximity or document importance. AU - Agrawal, Sanjay AU - Chakrabarti, Kaushik AU - Chaudhuri, Surajit AU - Ganti, Venkatesh AU - Konig, Arnd AU - Xin, Dong PY - 2009/// UR - http://dx.doi.org/10.1145/1526709.1526777 ER -