Searching databases for sematically-related schemas

Authors:
Gauri Shah;Tanveer Syeda-Mahmood
Affiliations:
IBM Almaden Research Center, San Jose, CA;IBM Almaden Research Center, San Jose, CA
Venue:
Proceedings of the 27th annual international ACM SIGIR conference on Research and development in information retrieval
Year:
2004

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Abstract

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.