Text mining: Difference between revisions
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imported>Robert Badgett (New page: '''Text mining''' "involves analysing a large collection of documents to discover previously unknown information".<ref name="titleText Mining briefing paper : JISC">{{cite web |url=http:...) |
imported>Robert Badgett No edit summary |
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'''Text mining''' "involves analysing a large collection of documents to discover previously unknown information".<ref name="titleText Mining briefing paper : JISC">{{cite web |url=http://www.jisc.ac.uk/publications/publications/pub_textmining.aspx |title=Text Mining briefing paper : JISC |accessdate=2008-01-22 |author= |authorlink= |coauthors= |date= |format= |work= |publisher= |pages= |language= |archiveurl= |archivedate= |quote=}}</ref> | '''Text mining''' "involves analysing a large collection of documents to discover previously unknown information".<ref name="titleText Mining briefing paper : JISC">{{cite web |url=http://www.jisc.ac.uk/publications/publications/pub_textmining.aspx |title=Text Mining briefing paper : JISC |accessdate=2008-01-22 |author= |authorlink= |coauthors= |date= |format= |work= |publisher= |pages= |language= |archiveurl= |archivedate= |quote=}}</ref> | ||
Coping with the many ways that a concept may be expressed in text (Zipf's law) remains a barrier in achieving results with text mining that are as good a human-curated results.<ref name="pmid15719064">{{cite journal |author=Rebholz-Schuhmann D, Kirsch H, Couto F |title=Facts from text--is text mining ready to deliver? |journal=PLoS Biol. |volume=3 |issue=2 |pages=e65 |year=2005 |pmid=15719064 |doi=10.1371/journal.pbio.0030065 |issn=}[http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=548955 PubMed Central]</ref> | Coping with the many ways that a concept may be expressed in text (Zipf's law) remains a barrier in achieving results with text mining that are as good a human-curated results.<ref name="pmid15719064">{{cite journal |author=Rebholz-Schuhmann D, Kirsch H, Couto F |title=Facts from text--is text mining ready to deliver? |journal=PLoS Biol. |volume=3 |issue=2 |pages=e65 |year=2005 |pmid=15719064 |doi=10.1371/journal.pbio.0030065 |issn=}}[http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=548955 PubMed Central]</ref> | ||
==References== | ==References== | ||
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==External links== | ==External links== | ||
National Institute | * National Institute of Standards and Technology's (NIST) Information Technology Laboratory (ITL): [http://www.itl.nist.gov/iaui/894.02/related_projects/muc/ Introduction to Information Extraction] | ||
[[Category:CZ Live]] [[Category:Library and Information Science Workgroup]] | [[Category:CZ Live]] [[Category:Library and Information Science Workgroup]] | ||
Revision as of 14:07, 22 January 2008
Text mining "involves analysing a large collection of documents to discover previously unknown information".[1]
Coping with the many ways that a concept may be expressed in text (Zipf's law) remains a barrier in achieving results with text mining that are as good a human-curated results.[2]
References
- ↑ Text Mining briefing paper : JISC. Retrieved on 2008-01-22.
- ↑ Rebholz-Schuhmann D, Kirsch H, Couto F (2005). "Facts from text--is text mining ready to deliver?". PLoS Biol. 3 (2): e65. DOI:10.1371/journal.pbio.0030065. PMID 15719064. Research Blogging. PubMed Central
External links
- National Institute of Standards and Technology's (NIST) Information Technology Laboratory (ITL): Introduction to Information Extraction