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Conference Paper

Semantic Full-Text Search with ESTER: Scalable, Easy, Fast

MPS-Authors
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Bast,  Holger
Algorithms and Complexity, MPI for Informatics, Max Planck Society;

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Suchanek,  Fabian
Databases and Information Systems, MPI for Informatics, Max Planck Society;

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Weber,  Ingmar
Algorithms and Complexity, MPI for Informatics, Max Planck Society;

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Citation

Bast, H., Suchanek, F., & Weber, I. (2008). Semantic Full-Text Search with ESTER: Scalable, Easy, Fast. In F. Bonchi, B. Berendt, F. Giannotti, D. Gunopulos, F. Turini, C. Zaniolo, et al. (Eds.), ICDM Workshops 2008 (pp. 959-962). Piscataway, NJ: IEEE. doi:10.1109/ICDMW.2008.101.


Cite as: https://hdl.handle.net/11858/00-001M-0000-000F-1CE8-7
Abstract
We present a demo of ESTER, a search engine that combines the ease of use, speed and scalability of full-text search with the powerful semantic capabilities of ontologies. % ESTER supports full-text queries, ontological queries and combinations of these, yet its interface is as easy as can be: A standard search field with semantic information provided interactively as one types. % ESTER works by reducing all queries to two basic operations: prefix search and join, which can be implemented very efficiently in terms of both processing time and index space. % We demonstrate the capabilities of ESTER on a combination of the English Wikipedia with the Yago ontology, with response times below 100 milliseconds for most queries, and an index size of about 4 GB. The system can be run both stand-alone and as a Web application.