Extracting named entities and relating them over time based on Wikipedia

From WikiLit
Jump to: navigation, search
Publication (help)
Extracting named entities and relating them over time based on Wikipedia
Authors: Abhijit Bhole, Blaž Fortuna, Marko Grobelnik, Dunja Mladenic [edit item]
Citation: Informatica 31 (4): 463-468. 2007.
Publication type: Journal article
Peer-reviewed: Yes
Database(s):
DOI: Define doi.
Google Scholar cites: Citations
Link(s): Paper link
Added by Wikilit team: Added on initial load
Search
Article: Google Scholar BASE PubMed
Other scholarly wikis: AcaWiki Brede Wiki WikiPapers
Web search: Bing Google Yahoo!Google PDF
Other:
Services
Format: BibTeX
Extracting named entities and relating them over time based on Wikipedia is a publication by Abhijit Bhole, Blaž Fortuna, Marko Grobelnik, Dunja Mladenic.


[edit] Abstract

This paper presents an approach to mining information relating people, places, organizations and events extracted from Wikipedia and linking them on a time scale. The approach consists of two phases: (1) identifying relevant pages - categorizing the articles as containing people, places or organizations; (2) generating timeline - linking named entities and extracting events and their time frame. We illustrate the proposed approach on 1.7 million Wikipedia articles.

[edit] Research questions

"This paper presents an approach to mining information relating people, places, organizations and events extracted from Wikipedia and linking them on a time scale. The approach consists of two phases: (1) identifying relevant pages - categorizing the articles as containing people, places or organizations; (2) generating timeline - linking named entities and extracting events and their time frame. We illustrate the proposed approach on 1.7 million Wikipedia articles."

Research details

Topics: Data mining, Technical infrastructure [edit item]
Domains: Computer science [edit item]
Theory type: Design and action [edit item]
Wikipedia coverage: Main topic [edit item]
Theories: "Undetermined" [edit item]
Research design: Experiment [edit item]
Data source: Experiment responses, Wikipedia pages [edit item]
Collected data time dimension: Cross-sectional [edit item]
Unit of analysis: Article [edit item]
Wikipedia data extraction: Live Wikipedia [edit item]
Wikipedia page type: Article [edit item]
Wikipedia language: Not specified [edit item]

[edit] Conclusion

"In this paper we outlined how heuristic based approaches can be used for extracting high quality annotations of Wikipedia articles and that automatic text categorization is a viable way of generalizing the heuristics. We have proposed an approach to that consist of two phases: (1) identifying relevant pages containing people, places or organizations and (2) generating timeline linking named entities via the extracting events and their time frame."

[edit] Comments

"We outlined how heuristic based approaches can be used for extracting high quality annotations of Wikipedia articles"


Further notes[edit]

Facts about "Extracting named entities and relating them over time based on Wikipedia"RDF feed
AbstractThis paper presents an approach to mining This paper presents an approach to mining information relating people, places, organizations and events extracted from Wikipedia and linking them on a time scale. The approach consists of two phases: (1) identifying relevant pages - categorizing the articles as containing people, places or organizations; (2) generating timeline - linking named entities and extracting events and their time frame. We illustrate the proposed approach on 1.7 million Wikipedia articles.pproach on 1.7 million Wikipedia articles.
Added by wikilit teamAdded on initial load +
Collected data time dimensionCross-sectional +
CommentsWe outlined how heuristic based approaches can be used for extracting high quality annotations of Wikipedia articles
ConclusionIn this paper we outlined how heuristic baIn this paper we outlined how heuristic based

approaches can be used for extracting high quality annotations of Wikipedia articles and that automatic text categorization is a viable way of generalizing the heuristics. We have proposed an approach to that consist of two phases: (1) identifying relevant pages containing people, places or organizations and (2) generating timeline linking named entities via the extracting events and their time frame.he extracting events

and their time frame.
Data sourceExperiment responses + and Wikipedia pages +
Google scholar urlhttp://scholar.google.com/scholar?ie=UTF-8&q=%22Extracting%2Bnamed%2Bentities%2Band%2Brelating%2Bthem%2Bover%2Btime%2Bbased%2Bon%2BWikipedia%22 +
Has authorAbhijit Bhole +, Blaž Fortuna +, Marko Grobelnik + and Dunja Mladenic +
Has domainComputer science +
Has topicData mining + and Technical infrastructure +
Issue4 +
Pages463-468 +
Peer reviewedYes +
Publication typeJournal article +
Published inInformatica +
Research designExperiment +
Research questionsThis paper presents an approach to mining This paper presents an approach to mining information relating people, places, organizations and

events extracted from Wikipedia and linking them on a time scale. The approach consists of two phases: (1) identifying relevant pages - categorizing the articles as containing people, places or organizations; (2) generating timeline - linking named entities and extracting events and their time frame. We illustrate

the proposed approach on 1.7 million Wikipedia articles.
pproach on 1.7 million Wikipedia articles.
Revid10,768 +
TheoriesUndetermined
Theory typeDesign and action +
TitleExtracting named entities and relating them over time based on Wikipedia
Unit of analysisArticle +
Urlhttp://www.freepatentsonline.com/article/Informatica/176867755.html +
Volume31 +
Wikipedia coverageMain topic +
Wikipedia data extractionLive Wikipedia +
Wikipedia languageNot specified +
Wikipedia page typeArticle +
Year2007 +