Article | Proceedings of the 19th Nordic Conference of Computational Linguistics (NODALIDA 2013); May 22-24; 2013; Oslo University; Norway. NEALT Proceedings Series 16 | Using Factual Density to Measure Informativeness of Web Documents Link�ping University Electronic Press Conference Proceedings
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Title:
Using Factual Density to Measure Informativeness of Web Documents
Author:
Chrstopher Horn: Know-Center GmbH, Graz, Austria Alisa Zhila: Centro de Investigación en Computación, Instituto Politåcnico Nacional, Mexico City, Mexico Alexander Gelbukh: Centro de Investigación en Computación, Instituto Politåcnico Nacional, Mexico City, Mexico Roman Kern: Know-Center GmbH, Graz, Austria Elisabeth Lex: Know-Center GmbH, Graz, Austria
Download:
Full text (pdf)
Year:
2013
Conference:
Proceedings of the 19th Nordic Conference of Computational Linguistics (NODALIDA 2013); May 22-24; 2013; Oslo University; Norway. NEALT Proceedings Series 16
Issue:
085
Article no.:
021
Pages:
227-238
No. of pages:
12
Publication type:
Abstract and Fulltext
Published:
2013-05-17
ISBN:
978-91-7519-589-6
Series:
Linköping Electronic Conference Proceedings
ISSN (print):
1650-3686
ISSN (online):
1650-3740
Series:
NEALT Proceedings Series
Publisher:
Linköping University Electronic Press; Linköpings universitet


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The information obtained from the Web is increasingly important for decision making and for our everyday tasks. Due to the growth of uncertified sources; blogosphere; comments in the social media and automatically generated texts; the need to measure the quality of text information found on the Internet is becoming of crucial importance. It has been suggested that factual density can be used to measure the informativeness of text documents. However; this was only shown on very specific texts such as Wikipedia articles. In this work we move to the sphere of the arbitrary Internet texts and show that factual density is applicable to measure the informativeness of textual contents of arbitrary Web documents. For this; we compiled a human-annotated reference corpus to be used as ground truth data to measure the adequacy of automatic prediction of informativeness of documents. Our corpus consists of 50 documents randomly selected from the Web; which were ranked by 13 human annotators using the MaxDiff technique. Then we ranked the same documents automatically using ExtrHech; an open information extraction system. The two rankings correlate; with Spearman’s coefficient ? = 0.41 at significance level of 99.64%.

Keywords: Quality of texts; Web; fact extraction; open information extraction; informativeness; natural language processing

Proceedings of the 19th Nordic Conference of Computational Linguistics (NODALIDA 2013); May 22-24; 2013; Oslo University; Norway. NEALT Proceedings Series 16

Author:
Chrstopher Horn, Alisa Zhila, Alexander Gelbukh, Roman Kern, Elisabeth Lex
Title:
Using Factual Density to Measure Informativeness of Web Documents
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Proceedings of the 19th Nordic Conference of Computational Linguistics (NODALIDA 2013); May 22-24; 2013; Oslo University; Norway. NEALT Proceedings Series 16

Author:
Chrstopher Horn, Alisa Zhila, Alexander Gelbukh, Roman Kern, Elisabeth Lex
Title:
Using Factual Density to Measure Informativeness of Web Documents
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