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Title: Extracting Chinese product features : representing a sequence by a set of skip-bigrams
Authors: Xu, G
Huang, CR 
Wang, H
Keywords: Product feature
Sentiment analysis
Word sequence
Issue Date: 2013
Source: Lecture notes in computer science (including subseries Lecture notes in artificial intelligence and Lecture notes in bioinformatics), 2013, v. 7717 LNAI, p. 72-83 How to cite?
Journal: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 
Abstract: A skip-bigram is a bigram that allows skips between words. In this paper, we use a set of skip bigrams (a SBGSet) to represent a short word sequence, which is the typical form of a product feature. The advantage of SBGSet representation for word sequences is that we can convert between a sequence and a set. Under the SBGSet representation we can employ association rule mining to find frequent itemsets from which frequent product features can be extracted.For infrequent product features, we use a pattern-based method to extract them. A pattern is also represented by a SBGSet, and contains a variable that can be instantiated to a product feature.We use two data sets to evaluate our method. The experimental result shows that our method is suitable for extracting Chinese product features, and the pattern-based method to extract infrequent product features is effective.
Description: 13th Chinese Lexical Semantics Workshop, CLSW 2012, Wuhan, 6-8 July 2012
ISBN: 9783642363368
ISSN: 0302-9743
DOI: 10.1007/978-3-642-36337-5_9
Appears in Collections:Conference Paper

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