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A low-resources approach to Opinion Analysis: Machine Learning and Simple Approaches
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In: http://davidkirkevans.com/Publications_files/2007_05_NTCIR.pdf (2007)
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A low-resources approach to Opinion Analysis: Machine Learning and Simple Approaches
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In: http://research.nii.ac.jp/ntcir/workshop/OnlineProceedings6/NTCIR/66.pdf (2007)
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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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ABSTRACT Identifying Similarity in Text: Multi-Lingual Analysis for Summarization
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In: http://www1.cs.columbia.edu/nlp/theses/dave_evans.pdf (2005)
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Similarity-based Multilingual Multi-Document Summarization
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In: http://www.cs.columbia.edu/nlp/papers/2005/evans_al_05.pdf (2005)
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Columbia newsblaster: multilingual news summarization on the web
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In: http://www.cs.columbia.edu/%7Edevans/papers/mlNewsblaster.pdf (2004)
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A Platform for Multilingual News Summarization Paper ID: Multilingual-Summarization-CU
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In: http://www.cs.columbia.edu/techreports/cucs-014-03.pdf (2003)
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Abstract:
Under consideration for other conferences (specify)? No We have developed a multilingual version of Columbia Newsblaster as a testbed for multilingual multi-document summarization. The system collects, clusters, and summarizes news documents from sources all over the world daily. It crawls news sites in many different countries, written in different languages, extracts the news text from the HTML pages, uses a variety of methods to translate the documents for clustering and summarization, and produces an English summary for each cluster. The system is robust, running daily over real-world data. The multilingual version of Columbia Newsblaster provides a platform for testing different strategies for multilingual document clustering, and approaches for multilingual multi-document summarization. A Platform for Multilingual News Summarization We have developed a multilingual version of Columbia Newsblaster as a testbed for multilingual multi-document summarization. The system collects, clusters, and summarizes news documents from sources all over the world daily. It crawls news sites in many different countries, written in different languages, extracts the news text from the HTML pages, uses a variety of methods to translate the documents for clustering and summarization, and produces an English summary for each cluster. The system is robust, running daily over real-world data. The multilingual version of Columbia Newsblaster provides a platform for testing different strategies for multilingual document clustering, and approaches for multilingual multi-document summarization. 1
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Keyword:
multilingual; summarization
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URL: http://www.cs.columbia.edu/techreports/cucs-014-03.pdf
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.71.3069
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A Platform for Multilingual . . .
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In: http://www.cs.columbia.edu/~library/TR-repository/reports/reports-2003/cucs-014-03.ps.gz (2003)
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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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Opinion Analysis across languages: An Overview of and Observations from the NTCIR6 Opinion Analysis Pilot Task
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In: http://nlg18.csie.ntu.edu.tw:8080/opinion/clip2007.pdf
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Multi-lingual Opinion Analysis Applied to World News: A Case Study
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In: http://davidkirkevans.com/Publications_files/2007.03.jnlp.pdf
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