Difference between revisions of "A knowledge-based search engine powered by Wikipedia"

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Revision as of 18:40, October 18, 2013

Publication (help)
A knowledge-based search engine powered by Wikipedia
Authors: David N. Milne, Ian H. Witten, David M. Nichols [edit item]
Citation: CIKM '07 Proceedings of the sixteenth ACM conference on Conference on information and knowledge management  : 445-454. 2007 November 6-9. Lisboa, Portugal. Association for Computing Machinery.
Publication type: Conference paper
Peer-reviewed: Yes
Database(s):
DOI: 10.1145/1321440.1321504.
Google Scholar cites: Citations
Link(s): Paper link
Added by Wikilit team: Added on initial load
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A knowledge-based search engine powered by Wikipedia is a publication by David N. Milne, Ian H. Witten, David M. Nichols.


[edit] Abstract

This paper describes Koru, a new search interface that offers effective domain-independent knowledge-based information retrieval. Koru exhibits an understanding of the topics of both queries and documents. This allows it to (a) expand queries automatically and (b) help guide the user as they evolve their queries interactively. Its understanding is mined from the vast investment of manual effort and judgment that is Wikipedia. We show how this open, constantly evolving encyclopedia can yield inexpensive knowledge structures that are specifically tailored to expose the topics, terminology and semantics of individual document collections. We conducted a detailed user study with 12 participants and 10 topics from the 2005 {TREC} {HARD} track, and found that Koru and its underlying knowledge base offers significant advantages over traditional keyword search. It was capable of lending assistance to almost every query issued to it; making their entry more efficient, improving the relevance of the documents they return, and narrowing the gap between expert and novice seekers. Copyright 2007 {ACM.}

[edit] Research questions

"This paper describes Koru, a new search interface that offers effective domain-independent knowledge-based information retrieval. Koru exhibits an understanding of the topics of both queries and documents. This allows it to (a) expand queries automatically and (b) help guide the user as they evolve their queries interactively. Its understanding is mined from the vast investment of manual effort and judgment that is Wikipedia. We show how this open, constantly evolving encyclopedia can yield inexpensive knowledge structures that are specifically tailored to expose the topics, terminology and semantics of individual document collections. We conducted a detailed user study with 12 participants and 10 topics from the 2005 TREC HARD track, and found that Koru and its underlying knowledge base offers significant advantages over traditional keyword search. It was capable of lending assistance to almost every query issued to it; making their entry more efficient, improving the relevance of the documents they return, and narrowing the gap between expert and novice seekers."

Research details

Topics: Query processing [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: [edit item]
Collected data time dimension: Cross-sectional [edit item]
Unit of analysis: User [edit item]
Wikipedia data extraction: Clone [edit item]
Wikipedia page type: N/A [edit item]
Wikipedia language: Not specified [edit item]

[edit] Conclusion

"This paper has introduced Koru, a new search engine that harnesses Wikipedia to provide domain-independent knowledgebased retrieval. Our intuition that Wikipedia could provide a knowledge base that matched both documents and queries has so far been borne out. We have tested it with a varied domainindependent collection of documents and retrieval tasks, and it was able to recognize and lend assistance to almost all queries issued to it, and significantly improve retrieval performance. Koru’s design was also validated, in that it allowed users to apply the knowledge found in Wikipedia to their retrieval process easily, effectively and efficiently. The following quote, given by one participant at the conclusion of their session, summarizes Koru’s performance best: It feels like a more powerful searching method, and allows you to search for topics that you may not have thought of… …it could use some improvements but the ability to graphically turn topics on/off is useful, and the way the system compresses synonymous terms together saves the user from having to search for the variations themselves. The ability to see a list of related terms also makes it easier to refine a search, where as with keyword searching you have to think up related terms yourself."

[edit] Comments

""[Wikipedia was tested] with a varied domain independent collection of documents and retrieval tasks, and it was able to recognize and lend assistance to almost all queries issued to it, and significantly improve retrieval performance." p. 453 search results"


Further notes[edit]

Facts about "A knowledge-based search engine powered by Wikipedia"RDF feed
AbstractThis paper describes Koru, a new search inThis paper describes Koru, a new search interface that offers effective domain-independent knowledge-based information retrieval. Koru exhibits an understanding of the topics of both queries and documents. This allows it to (a) expand queries automatically and (b) help guide the user as they evolve their queries interactively. Its understanding is mined from the vast investment of manual effort and judgment that is Wikipedia. We show how this open, constantly evolving encyclopedia can yield inexpensive knowledge structures that are specifically tailored to expose the topics, terminology and semantics of individual document collections. We conducted a detailed user study with 12 participants and 10 topics from the 2005 {TREC} {HARD} track, and found that Koru and its underlying knowledge base offers significant advantages over traditional keyword search. It was capable of lending assistance to almost every query issued to it; making their entry more efficient, improving the relevance of the documents they return, and narrowing the gap between expert and novice seekers. Copyright 2007 {ACM.} and novice seekers. Copyright 2007 {ACM.}
Added by wikilit teamAdded on initial load +
Collected data time dimensionCross-sectional +
Comments"[Wikipedia was tested] with a varied doma"[Wikipedia was tested] with a varied domain independent collection of documents and retrieval tasks, and it was able to recognize and lend assistance to almost all queries issued to it, and significantly improve retrieval performance." p. 453

search resultsrieval performance." p. 453

search results
ConclusionThis paper has introduced Koru, a new searThis paper has introduced Koru, a new search engine that

harnesses Wikipedia to provide domain-independent knowledgebased retrieval. Our intuition that Wikipedia could provide a knowledge base that matched both documents and queries has so far been borne out. We have tested it with a varied domainindependent collection of documents and retrieval tasks, and it was able to recognize and lend assistance to almost all queries issued to it, and significantly improve retrieval performance. Koru’s design was also validated, in that it allowed users to apply the knowledge found in Wikipedia to their retrieval process easily, effectively and efficiently. The following quote, given by one participant at the conclusion of their session, summarizes Koru’s performance best: It feels like a more powerful searching method, and allows you to search for topics that you may not have thought of… …it could use some improvements but the ability to graphically turn topics on/off is useful, and the way the system compresses synonymous terms together saves the user from having to search for the variations themselves. The ability to see a list of related terms also makes it easier to refine a search, where as with keyword searching you have to think up related terms yourself.u have to think up

related terms yourself.
Conference locationLisboa, Portugal +
Dates6-9 +
Doi10.1145/1321440.1321504 +
Google scholar urlhttp://scholar.google.com/scholar?ie=UTF-8&q=%22A%2Bknowledge-based%2Bsearch%2Bengine%2Bpowered%2Bby%2BWikipedia%22 +
Has authorDavid N. Milne +, Ian H. Witten + and David M. Nichols +
Has domainComputer science +
Has topicQuery processing +
MonthNovember +
Pages445-454 +
Peer reviewedYes +
Publication typeConference paper +
Published inCIKM '07 Proceedings of the sixteenth ACM conference on Conference on information and knowledge management +
PublisherAssociation for Computing Machinery +
Research designExperiment +
Research questionsThis paper describes Koru, a new search inThis paper describes Koru, a new search interface that offers

effective domain-independent knowledge-based information retrieval. Koru exhibits an understanding of the topics of both queries and documents. This allows it to (a) expand queries automatically and (b) help guide the user as they evolve their queries interactively. Its understanding is mined from the vast investment of manual effort and judgment that is Wikipedia. We show how this open, constantly evolving encyclopedia can yield inexpensive knowledge structures that are specifically tailored to expose the topics, terminology and semantics of individual document collections. We conducted a detailed user study with 12 participants and 10 topics from the 2005 TREC HARD track, and found that Koru and its underlying knowledge base offers significant advantages over traditional keyword search. It was capable of lending assistance to almost every query issued to it; making their entry more efficient, improving the relevance of the documents they return, and narrowing the gap between expert and novice seekers.the gap between expert and

novice seekers.
Revid9,823 +
TheoriesUndetermined
Theory typeDesign and action +
TitleA knowledge-based search engine powered by Wikipedia
Unit of analysisUser +
Urlhttp://researchcommons.waikato.ac.nz/handle/10289/5379 +
Wikipedia coverageSample data +
Wikipedia data extractionClone +
Wikipedia languageNot specified +
Wikipedia page typeN/A +
Year2007 +