A highly scalable and effective method for metasearch
ACM Transactions on Information Systems (TOIS)
Generic Schema Matching with Cupid
Proceedings of the 27th International Conference on Very Large Data Bases
Visual Web Information Extraction with Lixto
Proceedings of the 27th International Conference on Very Large Data Bases
Global Schema Generation Using Formal Ontologies
ER '02 Proceedings of the 21st International Conference on Conceptual Modeling
A survey of approaches to automatic schema matching
The VLDB Journal — The International Journal on Very Large Data Bases
Automatic integration of Web search interfaces with WISE-Integrator
The VLDB Journal — The International Journal on Very Large Data Bases
Semantic integration: a survey of ontology-based approaches
ACM SIGMOD Record
Fully automatic wrapper generation for search engines
WWW '05 Proceedings of the 14th international conference on World Wide Web
Schema and ontology matching with COMA++
Proceedings of the 2005 ACM SIGMOD international conference on Management of data
Constructing interface schemas for search interfaces of web databases
WISE'05 Proceedings of the 6th international conference on Web Information Systems Engineering
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We have developed a configurable meta-search engine for the human resource domain which aims to aid job seekers in searching for job vacancies and to support meta-search providers in the rapid development of meta-search engines. A significant challenge in accessing heterogeneous, distributed information via meta-search engines is the schema/data matching and integration that is needed for resolving semantic heterogeneities between different source search engines. We adopt a hybrid approach, using multiple matching criteria and matchers. A domain-specific ontology serves as a global ontology. Mappings are derived between this and the source search engine interfaces. These mappings are used to generate an integrated meta-search query interface, support query processing in the meta-search engine, and resolve semantic conflicts arising during result extraction from the source search engines. Experiments conducted in the job search domain show that our hybrid approach increases the correctness of matching during the integration of source search interfaces.