Company mention detection for large scale text mining

Rebecca Jane Passonneau, Tifara Ramelson, Boyi Xie

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Text mining on a large scale that addresses actionable prediction needs to contend with noisy information in documents, and with interdependencies between the NLP techniques applied and the data representation. This paper presents an initial investigation of the impact of improved company mention detection for financial analytics using Named Entity recognition and coreference. Coverage of company mention detection improves dramatically. Improvement for prediction of stock price varies, depending on the data representation.

Original languageEnglish (US)
Title of host publicationKDIR 2014 - Proceedings of the International Conference on Knowledge Discovery and Information Retrieval
EditorsJoaquim Filipe, Joaquim Filipe, Ana Fred
PublisherINSTICC Press
Pages512-520
Number of pages9
ISBN (Electronic)9789897580482
StatePublished - Jan 1 2014
Event6th International Conference on Knowledge Discovery and Information Retrieval, KDIR 2014 - Rome, Italy
Duration: Oct 21 2014Oct 24 2014

Publication series

NameKDIR 2014 - Proceedings of the International Conference on Knowledge Discovery and Information Retrieval

Other

Other6th International Conference on Knowledge Discovery and Information Retrieval, KDIR 2014
CountryItaly
CityRome
Period10/21/1410/24/14

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Industry

All Science Journal Classification (ASJC) codes

  • Information Systems
  • Computer Science Applications

Cite this

Passonneau, R. J., Ramelson, T., & Xie, B. (2014). Company mention detection for large scale text mining. In J. Filipe, J. Filipe, & A. Fred (Eds.), KDIR 2014 - Proceedings of the International Conference on Knowledge Discovery and Information Retrieval (pp. 512-520). (KDIR 2014 - Proceedings of the International Conference on Knowledge Discovery and Information Retrieval). INSTICC Press.
Passonneau, Rebecca Jane ; Ramelson, Tifara ; Xie, Boyi. / Company mention detection for large scale text mining. KDIR 2014 - Proceedings of the International Conference on Knowledge Discovery and Information Retrieval. editor / Joaquim Filipe ; Joaquim Filipe ; Ana Fred. INSTICC Press, 2014. pp. 512-520 (KDIR 2014 - Proceedings of the International Conference on Knowledge Discovery and Information Retrieval).
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abstract = "Text mining on a large scale that addresses actionable prediction needs to contend with noisy information in documents, and with interdependencies between the NLP techniques applied and the data representation. This paper presents an initial investigation of the impact of improved company mention detection for financial analytics using Named Entity recognition and coreference. Coverage of company mention detection improves dramatically. Improvement for prediction of stock price varies, depending on the data representation.",
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Passonneau, RJ, Ramelson, T & Xie, B 2014, Company mention detection for large scale text mining. in J Filipe, J Filipe & A Fred (eds), KDIR 2014 - Proceedings of the International Conference on Knowledge Discovery and Information Retrieval. KDIR 2014 - Proceedings of the International Conference on Knowledge Discovery and Information Retrieval, INSTICC Press, pp. 512-520, 6th International Conference on Knowledge Discovery and Information Retrieval, KDIR 2014, Rome, Italy, 10/21/14.

Company mention detection for large scale text mining. / Passonneau, Rebecca Jane; Ramelson, Tifara; Xie, Boyi.

KDIR 2014 - Proceedings of the International Conference on Knowledge Discovery and Information Retrieval. ed. / Joaquim Filipe; Joaquim Filipe; Ana Fred. INSTICC Press, 2014. p. 512-520 (KDIR 2014 - Proceedings of the International Conference on Knowledge Discovery and Information Retrieval).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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AB - Text mining on a large scale that addresses actionable prediction needs to contend with noisy information in documents, and with interdependencies between the NLP techniques applied and the data representation. This paper presents an initial investigation of the impact of improved company mention detection for financial analytics using Named Entity recognition and coreference. Coverage of company mention detection improves dramatically. Improvement for prediction of stock price varies, depending on the data representation.

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Passonneau RJ, Ramelson T, Xie B. Company mention detection for large scale text mining. In Filipe J, Filipe J, Fred A, editors, KDIR 2014 - Proceedings of the International Conference on Knowledge Discovery and Information Retrieval. INSTICC Press. 2014. p. 512-520. (KDIR 2014 - Proceedings of the International Conference on Knowledge Discovery and Information Retrieval).