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In this paper, we address the problem of searching schema databases for semantically-related schemas. We first give a method of finding semantic similarity between pair-wise schemas based on tokenization, part-of-speech tagging, word expansion, and ontology matching. We then address the problem of indexing the schema database through a semantic hash table. Matching schemas in the database are found by hashing the query attributes and recording peaks in the histogram of schema hits. Results indicated a 90% improvement in search performance while maintaining high precision and recall.
@inproceedings{1009092, author = {Gauri Shah and Tanveer Syeda-Mahmood}, title = {Searching databases for sematically-related schemas}, 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 = {504--505}, location = {Sheffield, United Kingdom}, doi = {http://doi.acm.org/10.1145/1008992.1009092}, publisher = {ACM Press}, }  ©2005 Association for Computing Machinery |
