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Extracting related named entities from blogosphere for event mining

Published: 31 January 2008 Publication History

Abstract

We propose a method of extracting named entities that are related to a single input word. Focusing on the syntactic dependency relation in sentences, it is reasonable to extract a case element that syntactically depends on the predicate that the input word depends on. In Japanese, though, a word which has appeared in a previous sentence is often omitted or replaced. Our proposed method, first, extracts "predicate patterns" consisting of case elements with case particles and a predicate. Then it combines predicate patterns that have the same predicate to form possible unabridged dependence relations.

References

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R. Iida, K. Inui and Y. Matsumoto. Exploiting Syntactic Patterns as Clues in Zero-Anaphora Resolution. In Proceedings of the 21st International Conference on Computational Linguistics and 44th Annual Meeting of the Association for Computational Linguistics, pp.625--632, 2006.
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Cited By

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  • (2018)Multi-modal multi-layered topic classification model for social event analysisMultimedia Tools and Applications10.1007/s11042-017-5588-777:18(23291-23315)Online publication date: 1-Sep-2018
  • (2015)Social Event Classification via Boosted Multimodal Supervised Latent Dirichlet AllocationACM Transactions on Multimedia Computing, Communications, and Applications10.1145/265952111:2(1-22)Online publication date: 7-Jan-2015
  • (2010)Generating an event arrangement for understanding news articles on the webProceedings of the 23rd international conference on Industrial engineering and other applications of applied intelligent systems - Volume Part II10.5555/1945847.1945910(525-534)Online publication date: 1-Jun-2010
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cover image ACM Conferences
ICUIMC '08: Proceedings of the 2nd international conference on Ubiquitous information management and communication
January 2008
604 pages
ISBN:9781595939937
DOI:10.1145/1352793
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Publication History

Published: 31 January 2008

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Author Tags

  1. information extraction
  2. text mining
  3. world wide web

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Cited By

View all
  • (2018)Multi-modal multi-layered topic classification model for social event analysisMultimedia Tools and Applications10.1007/s11042-017-5588-777:18(23291-23315)Online publication date: 1-Sep-2018
  • (2015)Social Event Classification via Boosted Multimodal Supervised Latent Dirichlet AllocationACM Transactions on Multimedia Computing, Communications, and Applications10.1145/265952111:2(1-22)Online publication date: 7-Jan-2015
  • (2010)Generating an event arrangement for understanding news articles on the webProceedings of the 23rd international conference on Industrial engineering and other applications of applied intelligent systems - Volume Part II10.5555/1945847.1945910(525-534)Online publication date: 1-Jun-2010
  • (2010)Relation Extraction between Related Concepts by Combining Wikipedia and Web Information for Japanese LanguageInformation Retrieval Technology10.1007/978-3-642-17187-1_30(310-319)Online publication date: 2010
  • (2010)Generating an Event Arrangement for Understanding News Articles on the WebTrends in Applied Intelligent Systems10.1007/978-3-642-13025-0_54(525-534)Online publication date: 2010

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