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The larger amount of information on the Web is stored in document databases and is not indexed by general-purpose search engines (i.e., Google and Yahoo). Such information is dynamically generated through querying databases - which are referred to as Hidden Web databases. Documents returned in response to a user query are typically presented using template-generated Web pages. This paper proposes a novel approach that identifies Web page templates by analysing the textual contents and the adjacent tag structures of a document in order to extract query-related data. Preliminary results demonstrate that our approach effectively detects templates and retrieves data with high recall and precision.
@inproceedings{1009119, author = {Y. L. Hedley and M. Younas and A. James and M. Sanderson}, title = {Query-related data extraction of hidden web documents}, booktitle = {SIGIR '04: Proceedings of the 27th annual international conference on Research and development in information retrieval}, year = {2004}, isbn = {1-58113-881-4}, pages = {558--559}, location = {Sheffield, United Kingdom}, doi = {http://doi.acm.org/10.1145/1008992.1009119}, publisher = {ACM Press}, }  ©2005 Association for Computing Machinery |
