A tutorial on hidden Markov models and selected applications in speech recognition
Readings in speech recognition
A language modeling approach to information retrieval
Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval
Parsimonious language models for information retrieval
Proceedings of the 27th annual international ACM SIGIR conference on Research and development in information retrieval
Generating query substitutions
Proceedings of the 15th international conference on World Wide Web
Term context models for information retrieval
CIKM '06 Proceedings of the 15th ACM international conference on Information and knowledge management
COLING '04 Proceedings of the 20th international conference on Computational Linguistics
CCGbank: A Corpus of CCG Derivations and Dependency Structures Extracted from the Penn Treebank
Computational Linguistics
Sentiment analysis in multiple languages: Feature selection for opinion classification in Web forums
ACM Transactions on Information Systems (TOIS)
Opinion Mining and Sentiment Analysis
Foundations and Trends in Information Retrieval
Investigating Learning Approaches for Blog Post Opinion Retrieval
ECIR '09 Proceedings of the 31th European Conference on IR Research on Advances in Information Retrieval
A study of inter-annotator agreement for opinion retrieval
Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval
Fully automatic lexicon expansion for domain-oriented sentiment analysis
EMNLP '06 Proceedings of the 2006 Conference on Empirical Methods in Natural Language Processing
Recognizing contextual polarity: An exploration of features for phrase-level sentiment analysis
Computational Linguistics
A unified relevance model for opinion retrieval
Proceedings of the 18th ACM conference on Information and knowledge management
Automatic creation of a reference corpus for political opinion mining in user-generated content
Proceedings of the 1st international CIKM workshop on Topic-sentiment analysis for mass opinion
Domain-specific sentiment analysis using contextual feature generation
Proceedings of the 1st international CIKM workshop on Topic-sentiment analysis for mass opinion
The Probabilistic Relevance Framework: BM25 and Beyond
Foundations and Trends in Information Retrieval
Cross-domain sentiment classification via spectral feature alignment
Proceedings of the 19th international conference on World wide web
Optimizing two stage bigram language models for IR
Proceedings of the 19th international conference on World wide web
Proximity-based opinion retrieval
Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval
ACM SIGIR Forum
What computational linguists can learn from psychologists (and vice versa)
Computational Linguistics
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Existing opinion retrieval techniques do not provide context-dependent relevant results. Most of the approaches used by state-of-the-art techniques are based on frequency of query terms, such that all documents containing query terms are retrieved, regardless of contextual relevance to the intent of the human seeking the opinion. However, in a particular opinionated document, words could occur in different contexts, yet meet the frequency attached to a certain opinion threshold, thus explicitly creating a bias in overall opinion retrieved. In this paper we propose a sentence-level contextual model for opinion retrieval using grammatical tree derivations and approval voting mechanism. Model evaluation performed between our contextual model, BM25, and language model shows that the model can be effective for contextual opinion retrieval such as faceted opinion retrieval.