Extracting schema from semistructured data
SIGMOD '98 Proceedings of the 1998 ACM SIGMOD international conference on Management of data
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ACM SIGMOD Record
What Are Ontologies, and Why Do We Need Them?
IEEE Intelligent Systems
ICDT '97 Proceedings of the 6th International Conference on Database Theory
Expert Systems with Applications: An International Journal
Enhancement of domain ontology construction using a crystallizing approach
Expert Systems with Applications: An International Journal
Repurposing social tagging data for extraction of domain-level concepts
NLDB'11 Proceedings of the 16th international conference on Natural language processing and information systems
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The explosive growth of data on the web makes information management and knowledge discovery increasingly difficult. Applying database techniques to manage web information can help in solving these problems. One difficulty encountered is that web documents, unlike structured databases, contain unstructured and semi-structured data. Our hypothesis is that creating ontologies to describe the semantics of web data is the key to bridging the gap between semi-structured data and structured databases, and hence facilitating the application of database techniques. We extract an ontology (or conceptual schema) from a set of web pages in a particular application domain automatically. The prototype we are constructing is called WebOntEx for Web Ontology Extraction. This paper describes the data preparation process and the semantic resolution process of the WebOntEx project to build meta-database and web database.