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Traditional Chinese, and Simplified Chinese. Using
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In: http://nlg.csie.ntu.edu.tw/conference_papers/nntcir2008b.pdf (2008)
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Opinion analysis across languages: An overview of and observations from the ntcir6 opinion analysis pilot task
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In: http://nlg.csie.ntu.edu.tw/conference_papers/wilf2007.pdf (2007)
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Certainty categorization model
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In: http://www.cnlp.org/publications/04RubinKandoLiddy2004_Certainty.pdf (2004)
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Overview of clir task at the third ntcir workshop
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In: http://nlg.csie.ntu.edu.tw/conference_papers/ntcir2002a.pdf (2002)
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1. NTCIR Cross-Language Retrieval
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In: http://www.lrec-conf.org/proceedings/lrec2008/pdf/363_paper.pdf
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1. NTCIR Cross-Language Retrieval
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In: http://www.mt-archive.info/LREC-2008-Gey.pdf
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***Department of Statistics, Chungnam National University
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In: http://nlg3.csie.ntu.edu.tw/conference_papers/ntcir6clir.pdf
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M.: CRES at LogCLEF 2010: Towards understanding the user behaviors through an analysis of search sessions, search units and click ranks
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In: http://www.clef-initiative.eu/documents/71612/86374/CLEF2010wn-LogCLEF-TakakuEt2010.pdf
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***Department of Statistics, Chungnam National University
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In: http://research.nii.ac.jp/ntcir/workshop/OnlineProceedings6/NTCIR/79.pdf
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NTCIR-GeoTime Overview: Evaluating Geographic and Temporal Search
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In: http://research.nii.ac.jp/ntcir/workshop/OnlineProceedings8/NTCIR/01-NTCIR8-OV-GeoTime-GeyF.pdf
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Proceedingsof the Third NTCIR Workshop Overview of CLIR Task at the Third NTCIR Workshop
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In: http://research.nii.ac.jp/ntcir/workshop/OnlineProceedings3/NTCIR3-OV-CLIR-ChenK.rev.pdf
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***Department of Statistics, Chungnam National University
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In: http://nlg.csie.ntu.edu.tw/conference_papers/ntcir2005d.pdf
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Analysis of multi-document viewpoint summarization using multi-dimensional genres
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In: http://aaaipress.org/Papers/Symposia/Spring/2004/SS-04-07/SS04-07-026.pdf
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Abstract:
An interactive information retrieval system that pro-vides different types of summaries of retrieved docu-ments according to each user’s information needs can be effective for understanding the contents. The pur-pose of this study is to build a multi-document sum-marizer to produce summaries according to such view-points. As an exploratory stage of investigation, we ex-amined the effectiveness of genre for source documents to produce different types of summaries. Once a set of documents on a topic is provided to our summarization system, a list of topics discussed in the given document set is presented, so that the user can select a topic of in-terest from the list as well as the summary type, such as opinion-oriented, fact-reporting or knowledge-focused, according to their requirements. We assume a relation-ship between a summary type and human recognition of information types included in the source: a docu-ment genre. We also analyzed the results of the multi-document summarization using automatic genre classi-fication to reveal the association between genre dimen-sions and the summary types.
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URL: http://aaaipress.org/Papers/Symposia/Spring/2004/SS-04-07/SS04-07-026.pdf http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.462.6942
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