JU_CSE: A Conditional Random Field (CRF) Based Approach to Aspect Based Sentiment Analysis

The fast upswing of online reviews and their sentiments on the Web became very useful information to the people. Thus, the opinion/sentiment mining has been adopted as a subject of increasingly research interest in the recent years. Being a participant in the Shared Task Challenge, we have developed a Conditional Random Field based system to accomplish the Aspect Based Sentiment Analysis task. The aspect term in a sentence is defined as the target entity. The present system identifies aspect term, aspect categories and their sentiments from the Laptop and Restaurants review datasets provided by the organizers.

[1]  Carlo Strapparava,et al.  WordNet Affect: an Affective Extension of WordNet , 2004, LREC.

[2]  Oren Etzioni,et al.  Extracting Product Features and Opinions from Reviews , 2005, HLT.

[3]  Eduard Hovy,et al.  Extracting Opinions, Opinion Holders, and Topics Expressed in Online News Media Text , 2006 .

[4]  Braja Gopal Patra,et al.  Construction of Emotional Lexicon Using Potts Model , 2013, IJCNLP.

[5]  Dipankar Das,et al.  Extracting emotion topics from blog sentences: use of voting from multi-engine supervised classifiers , 2010, SMUC '10.

[6]  Koby Crammer,et al.  Pranking with Ranking , 2001, NIPS.

[7]  Amélie Marian,et al.  Beyond the Stars: Improving Rating Predictions using Review Text Content , 2009, WebDB.

[8]  Hua Xu,et al.  Clustering product features for opinion mining , 2011, WSDM '11.

[9]  Noémie Elhadad,et al.  An Unsupervised Aspect-Sentiment Model for Online Reviews , 2010, NAACL.

[10]  Andrea Esuli,et al.  SentiWordNet 3.0: An Enhanced Lexical Resource for Sentiment Analysis and Opinion Mining , 2010, LREC.

[11]  Hong Yu,et al.  Towards Answering Opinion Questions: Separating Facts from Opinions and Identifying the Polarity of Opinion Sentences , 2003, EMNLP.

[12]  Andrew McCallum,et al.  Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data , 2001, ICML.

[13]  Regina Barzilay,et al.  Multiple Aspect Ranking Using the Good Grief Algorithm , 2007, NAACL.

[14]  Bing Liu,et al.  Mining and summarizing customer reviews , 2004, KDD.

[15]  Suresh Manandhar,et al.  SemEval-2014 Task 4: Aspect Based Sentiment Analysis , 2014, *SEMEVAL.

[16]  Alice H. Oh,et al.  Aspect and sentiment unification model for online review analysis , 2011, WSDM '11.

[17]  Martin Ester,et al.  Opinion digger: an unsupervised opinion miner from unstructured product reviews , 2010, CIKM.