Ester: efficient search on text, entities, and relations

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Ester: efficient search on text, entities, and relations
Authors: Holger Bast, Alexandru Chitea, Fabian M. Suchanek, Ingmar Weber [edit item]
Citation: SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval  : 671-678. 2007 July 23-27. Amsterdam, Netherlands. Association for Computing Machinery.
Publication type: Conference paper
Peer-reviewed: Yes
Database(s):
DOI: 10.1145/1277741.1277856.
Google Scholar cites: Citations
Link(s): Paper link
Added by Wikilit team: Added on initial load
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Ester: efficient search on text, entities, and relations is a publication by Holger Bast, Alexandru Chitea, Fabian M. Suchanek, Ingmar Weber.


[edit] Abstract

We present ESTER, a modular and highly efficient system for combined full-text and ontology search. ESTER builds on a query engine that supports two basic operations: prefix search and join. Both of these can be implemented very efficiently with a compact index, yet in combination provide powerful querying capabilities. We show how ESTER can answer basic SPARQL graph-pattern queries on the ontology by reducing them to a small number of these two basic operations. ESTER further supports a natural blend of such semantic queries with ordinary full-text queries. Moreover, the prefix search operation allows for a fully interactive and proactive user interface, which after every keystroke suggests to the user possible semantic interpretations of his or her query, and speculatively executes the most likely of these interpretations. As a proof of concept, we applied ESTER to the English Wikipedia, which contains about 3 million documents, combined with the recent YAGO ontology, which contains about 2.5 million facts. For a variety of complex queries, ESTER achieves worst-case query processing times of a fraction of a second, on a single machine, with an index size of about 4 GB.

[edit] Research questions

"We present ESTER, a modular and highly efficient system for combined full-text and ontology search. ESTER builds on a query engine that supports two basic operations: prefix search and join. Both of these can be implemented very efficiently with a compact index, yet in combination provide powerful querying capabilities."

Research details

Topics: Textual information retrieval [edit item]
Domains: Computer science [edit item]
Theory type: Design and action [edit item]
Wikipedia coverage: Sample data [edit item]
Theories: "Undetermined" [edit item]
Research design: Experiment [edit item]
Data source: Experiment responses, Websites, Wikipedia pages [edit item]
Collected data time dimension: Cross-sectional [edit item]
Unit of analysis: Article [edit item]
Wikipedia data extraction: Dump [edit item]
Wikipedia page type: Article [edit item]
Wikipedia language: Not specified [edit item]

[edit] Conclusion

"We have seen that ESTER, our search engine for combined full-text and ontology search, scales very well to large amounts of data. For the Wikipedia collection combined with the YAGO ontology, ESTER can process a variety of complex queries in a fraction of a second, with an index size of only about 4 GB"

[edit] Comments

""For the Wikipedia collection combined with the YAGO ontology, [the proposed search engine] ESTER can process a variety of complex queries in a fraction of a second, with an index size of only about 4 GB." p. 678"


Further notes[edit]

Facts about "Ester: efficient search on text, entities, and relations"RDF feed
AbstractWe present ESTER, a modular and highly effWe present ESTER, a modular and highly efficient system for combined full-text and ontology search. ESTER builds on a query engine that supports two basic operations: prefix search and join. Both of these can be implemented very efficiently with a compact index, yet in combination provide powerful querying capabilities. We show how ESTER can answer basic SPARQL graph-pattern queries on the ontology by reducing them to a small number of these two basic operations. ESTER further supports a natural blend of such semantic queries with ordinary full-text queries. Moreover, the prefix search operation allows for a fully interactive and proactive user interface, which after every keystroke suggests to the user possible semantic interpretations of his or her query, and speculatively executes the most likely of these interpretations. As a proof of concept, we applied ESTER to the English Wikipedia, which contains about 3 million documents, combined with the recent YAGO ontology, which contains about 2.5 million facts. For a variety of complex queries, ESTER achieves worst-case query processing times of a fraction of a second, on a single machine, with an index size of about 4 GB.machine, with an index size of about 4 GB.
Added by wikilit teamAdded on initial load +
Collected data time dimensionCross-sectional +
Comments"For the Wikipedia collection combined with the YAGO ontology, [the proposed search engine] ESTER can process a variety of complex queries in a fraction of a second, with an index size of only about 4 GB." p. 678
ConclusionWe have seen that ESTER, our search engineWe have seen that ESTER, our search engine for combined

full-text and ontology search, scales very well to large amounts of data. For the Wikipedia collection combined with the YAGO ontology, ESTER can process a variety of complex queries in a fraction of a second, with an index size of only about 4 GBond, with an index size

of only about 4 GB
Conference locationAmsterdam, Netherlands +
Data sourceExperiment responses +, Websites + and Wikipedia pages +
Dates23-27 +
Doi10.1145/1277741.1277856 +
Google scholar urlhttp://scholar.google.com/scholar?ie=UTF-8&q=%22Ester%3A%2Befficient%2Bsearch%2Bon%2Btext%2C%2Bentities%2C%2Band%2Brelations%22 +
Has authorHolger Bast +, Alexandru Chitea +, Fabian M. Suchanek + and Ingmar Weber +
Has domainComputer science +
Has topicTextual information retrieval +
MonthJuly +
Pages671-678 +
Peer reviewedYes +
Publication typeConference paper +
Published inSIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval +
PublisherAssociation for Computing Machinery +
Research designExperiment +
Research questionsWe present ESTER, a modular and highly effWe present ESTER, a modular and highly efficient system

for combined full-text and ontology search. ESTER builds on a query engine that supports two basic operations: prefix search and join. Both of these can be implemented very efficiently with a compact index, yet in combination provide powerful querying capabilities.on provide

powerful querying capabilities.
Revid10,752 +
TheoriesUndetermined
Theory typeDesign and action +
TitleEster: efficient search on text, entities, and relations
Unit of analysisArticle +
Urlhttp://dl.acm.org/citation.cfm?id=1277856 +
Wikipedia coverageSample data +
Wikipedia data extractionDump +
Wikipedia languageNot specified +
Wikipedia page typeArticle +
Year2007 +