Ontology Based Opinion Mining for Movie Reviews

Ontology itself is an explicitly defined reference model of application domains with the purpose of improving information consistency and knowledge sharing. It describes the semantics of a domain in both human-understandable and computer-processable way. Motivated by its success in the area of Information Extraction (IE), we propose an ontology-based approach for opinion mining. In general, opinion mining is quite context-sensitive, and, at a coarser granularity, quite domain dependent. This paper introduces a fine-grain approach for opinion mining, which uses the ontology structure as an essential part of the feature extraction process, by taking account the relations between concepts. The experiment result shows the benefits of exploiting ontology structure to opinion mining.

[1]  Bo Pang,et al.  Thumbs up? Sentiment Classification using Machine Learning Techniques , 2002, EMNLP.

[2]  Giuseppe Carenini,et al.  Interactive multimedia summaries of evaluative text , 2006, IUI '06.

[3]  Giuseppe Mastronuzzi,et al.  Markers of the last interglacial sea-level high stand along the coast of Italy: Tectonic implications , 2006 .

[4]  Peter D. Turney Thumbs Up or Thumbs Down? Semantic Orientation Applied to Unsupervised Classification of Reviews , 2002, ACL.

[5]  Mauro De Donatis,et al.  Frontal part of the northern Apennines fold and thrust belt in the Romagna‐Marche area (Italy): Shallow and deep structural styles , 1999 .

[6]  Joost N. Kok,et al.  Advances in Intelligent Data Analysis VI, 6th International Symposium on Intelligent Data Analysis, IDA 2005, Madrid, Spain, September 8-10, 2005, Proceedings , 2005, IDA.

[7]  Bo Pang,et al.  Seeing Stars: Exploiting Class Relationships for Sentiment Categorization with Respect to Rating Scales , 2005, ACL.

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

[9]  Hiroshi Kanayama,et al.  Fully Automatic Lexicon Expansion for Domain-oriented Sentiment Analysis , 2006, EMNLP.

[10]  D. Wells,et al.  New empirical relationships among magnitude, rupture length, rupture width, rupture area, and surface displacement , 1994, Bulletin of the Seismological Society of America.

[11]  Gianluca Valensise,et al.  Defining seismogenic sources from historical earthquake felt reports , 1999, Bulletin of the Seismological Society of America.

[12]  Razvan C. Bunescu,et al.  Sentiment analyzer: extracting sentiments about a given topic using natural language processing techniques , 2003, Third IEEE International Conference on Data Mining.

[13]  Claudio Chiarabba,et al.  A new view of Italian seismicity using 20 years of instrumental recordings , 2005 .

[14]  D. L. Anderson,et al.  Theoretical Basis of Some Empirical Relations in Seismology by Hiroo Kanamori And , 1975 .

[15]  Ellen Riloff,et al.  Learning Extraction Patterns for Subjective Expressions , 2003, EMNLP.

[16]  Vasileios Hatzivassiloglou,et al.  Predicting the Semantic Orientation of Adjectives , 1997, ACL.

[17]  David M. Pennock,et al.  Mining the peanut gallery: opinion extraction and semantic classification of product reviews , 2003, WWW '03.

[18]  Bing Liu,et al.  The utility of linguistic rules in opinion mining , 2007, SIGIR.

[19]  Thomas R. Gruber,et al.  A translation approach to portable ontology specifications , 1993, Knowl. Acquis..

[20]  E. Guidoboni,et al.  Catalogue of earthquakes and tsunamis in the Mediterranean area from the 11th to the 15th century , 2005 .

[21]  Andrea Esuli,et al.  SENTIWORDNET: A Publicly Available Lexical Resource for Opinion Mining , 2006, LREC.

[22]  Masaru Kitsuregawa,et al.  Automatic Construction of Polarity-Tagged Corpus from HTML Documents , 2006, ACL.

[23]  Gianluca Valensise,et al.  Deformation of the 125 ka marine terrace in Italy: tectonic implications , 1999, Geological Society, London, Special Publications.

[24]  Eric K. Ringger,et al.  Pulse: Mining Customer Opinions from Free Text , 2005, IDA.

[25]  Yuji Matsumoto,et al.  Collecting Evaluative Expressions for Opinion Extraction , 2004, IJCNLP.

[26]  Y. Okada Surface deformation due to shear and tensile faults in a half-space , 1985 .

[27]  Maria Chiara Invernizzi,et al.  CROP 03: Structure of the Montecalvo in Foglia - Adriatic Sea Segment , 1998 .

[28]  Roberto Basili,et al.  New geomorphic evidence for anticlinal growth driven by blind-thrust faulting along the northern Marche coastal belt (central Italy) , 2004 .

[29]  D. P. Schwartz,et al.  Fault behavior and characteristic earthquakes: Examples from the Wasatch and San Andreas Fault Zones , 1984 .

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

[31]  Christian Jacquemin,et al.  Spotting and Discovering Terms through Natural Language Processing , 1997 .

[32]  Marti A. Hearst Direction-based text interpretation as an information access refinement , 1992 .

[33]  Bing Liu,et al.  Mining Opinion Features in Customer Reviews , 2004, AAAI.

[34]  James G. Ogg,et al.  A new Geologic Time Scale, with special reference to Precambrian and Neogene , 2004 .