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Simple Search
Hits 1 – 13 of 13
1
Construction of a sentimental word dictionary
Eduard C. Dragut
;
Clement Yu Prasad
;
Weiyi Meng
In: http://www.cs.binghamton.edu/~meng/pub.d/cikm785-dragut.pdf (2010)
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2
Recognition and classification of noun phrases in queries for effective retrieval
Wei Zhang
;
Shuang Liu
;
Clement Yu
...
In: http://www.cs.binghamton.edu/~meng/pub.d/p711-zhang-cikm07a.pdf (2005)
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3
Word sense disambiguation in queries
Shuang Liu
;
Clement Yu
In: http://www.cs.binghamton.edu/~meng/pub.d/cikm05Shuang.pdf (2005)
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4
Recognition and classification of noun phrases in queries for effective retrieval
Wei Zhang
;
Shuang Liu
;
Clement Yu
...
In: http://www.cs.uic.edu/~wzhang/cikm2007/zhang_cikm_2007_recognition.pdf (2005)
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5
An effective approach to document retrieval via utilizing wordnet and recognizing phrases
Shuang Liu
;
Fang Liu
;
Clement Yu
...
In: http://www.cs.binghamton.edu/~meng/pub.d/p266-liu.pdf (2004)
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6
An effective approach to document retrieval via utilizing wordnet and recognizing phrases
Shuang Liu
;
Fang Liu
;
Clement Yu
...
In: http://www.cs.uic.edu/~sliu/p096-liu.pdf (2004)
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7
Deriving Customized Integrated Web Query Interfaces
Eduard C. Dragut
;
Fang Fang
;
Clement Yu
...
In: http://www.cs.binghamton.edu/~meng/pub.d/WI09.pdf
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8
Faceted Models of Blog Feeds
Lifeng Jia
;
Clement Yu
;
Weiyi Meng
In: http://www.cs.binghamton.edu/~meng/pub.d/p2279-jia-cikm13.pdf
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9
Abstract UIC at TREC-2004: Robust Track
Shuang Liu
;
Chaojing Sun
;
Clement Yu
In: http://trec.nist.gov/pubs/trec13/papers/uil-chicago.liu.robust.pdf
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10
UIC at TREC 2010 Faceted Blog Distillation
Lifeng Jia
;
Clement Yu
In: http://trec.nist.gov/pubs/trec19/papers/univ.illinois-chicago.blog.rev2.pdf
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11
Abstract UIC at TREC-2003: Robust Track (Draft)
Shuang Liu
;
Clement Yu
In: http://trec.nist.gov/pubs/trec12/papers/uillinois-chicago.robust.pdf
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12
Topic Sentiment Change Analysis
Yu Jiang
;
Clement Yu
In: http://www.cs.binghamton.edu/~meng/pub.d/MLDM-camera_ready.pdf
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13
Polarity Consistency Checking for Domain Independent Sentiment Dictionaries
Eduard C. Dragut
;
Hong Wang
;
Prasad Sistla
;
Clement Yu
;
Weiyi Meng
In: http://www.cs.binghamton.edu/%7Emeng/pub.d/tkde-2015.pdf
Abstract:
Abstract—Polarity classification of words is important for applications such as Opinion Mining and Sentiment Analysis. A number of sentiment word/sense dictionaries have been manually or (semi)automatically constructed. We notice that these sentiment dictionaries have numerous inaccuracies. Besides obvious instances, where the same word appears with different polarities in different dictionaries, the dictionaries exhibit complex cases of polarity inconsistency, which cannot be detected by mere manual inspection. We introduce the concept of polarity consistency of words/senses in sentiment dictionaries in this paper. We show that the consistency problem is NP-complete. We reduce the polarity consistency problem to the satisfiability problem and utilize two fast SAT solvers to detect inconsistencies in a sentiment dictionary. We perform experiments on five sentiment dictionaries and WordNet to show inter- and intra-dictionaries inconsistencies. Index Terms—Sentiment analysis, sentiment dictionary, polarity inconsistency Ç 1
URL:
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.697.4013
http://www.cs.binghamton.edu/%7Emeng/pub.d/tkde-2015.pdf
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