Paper Info
Title
Identifying sentiment patterns of BBS reviews based on associateve memory model
Abstract
BBS is popular online forum, which contains a great wealth of knowledge about private opinions and sentiments. Because the information in BBS is mess, it is difficult to identify this useful knowledge. Taking advantage of the functions of bidirectional associative memory, the paper presents a novel method to identify sentiment patterns of BBS reviews. We call it ISPBAM (Identify Sentiment Patterns based on BAM). It can acquire the syntax pattern of unnormal sentences in BBS reviews and identify the sentiment orientation of them. So it combines two functions of sentiment classification and polar terms recognization. But differ from simplex sentiment classification or polar terms recognition, this method can identify sentiment patterns without constructing linguistic resources. The experiments are done for BBS reviews about recent Chinese Spring Festival Gala Evenings. The results show the proposed method is feasible, and more powerful than former methods.
Year
DOI
Venue
2010
10.1109/ICNC.2010.5582700
ICNC
Keywords
Field
DocType
sentiment pattern identification,bidirectional associative memory (bam),bbs reviews,artificial intelligence,linguistic resources,sentiment identification,pattern classification,text,syntax pattern,sentiment patterns (sp),associative memory model,bidirectional associative memory,sentiment classification,artificial neural network,online forum,natural language processing,polar term recognization,content-addressable storage,text analysis,neural nets,classification algorithms,artificial neural networks,memory model,pattern matching,associative memory,pragmatics
Content-addressable memory,Pragmatics,Bidirectional associative memory,Computer science,Sentiment analysis,Memory model,Natural language processing,Artificial intelligence,Statistical classification,Pattern matching,Syntax,Machine learning
Conference
Volume
ISBN
Citations 
4
978-1-4244-5958-2
0
PageRank 
References 
Authors
0.34
4
3
Name
Order
Citations
PageRank
Delan Xiong100.34
Shengli Tian2112.38
Bo-ping Zhang3103.65