Viewing morphology as an inference process
SIGIR '93 Proceedings of the 16th annual international ACM SIGIR conference on Research and development in information retrieval
A language modeling approach to information retrieval
Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval
A general language model for information retrieval
Proceedings of the eighth international conference on Information and knowledge management
Relevance based language models
Proceedings of the 24th annual international ACM SIGIR conference on Research and development in information retrieval
A study of smoothing methods for language models applied to Ad Hoc information retrieval
Proceedings of the 24th annual international ACM SIGIR conference on Research and development in information retrieval
Mining the peanut gallery: opinion extraction and semantic classification of product reviews
WWW '03 Proceedings of the 12th international conference on World Wide Web
Retrieval and novelty detection at the sentence level
Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval
Measuring praise and criticism: Inference of semantic orientation from association
ACM Transactions on Information Systems (TOIS)
Sentiment analysis: capturing favorability using natural language processing
Proceedings of the 2nd international conference on Knowledge capture
ICDM '03 Proceedings of the Third IEEE International Conference on Data Mining
Predicting the semantic orientation of adjectives
ACL '98 Proceedings of the 35th Annual Meeting of the Association for Computational Linguistics and Eighth Conference of the European Chapter of the Association for Computational Linguistics
Retrieval evaluation with incomplete information
Proceedings of the 27th annual international ACM SIGIR conference on Research and development in information retrieval
Mining and summarizing customer reviews
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
Thumbs up or thumbs down?: semantic orientation applied to unsupervised classification of reviews
ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
Computing Attitude and Affect in Text: Theory and Applications (The Information Retrieval Series)
Computing Attitude and Affect in Text: Theory and Applications (The Information Retrieval Series)
Thumbs up?: sentiment classification using machine learning techniques
EMNLP '02 Proceedings of the ACL-02 conference on Empirical methods in natural language processing - Volume 10
Determining the sentiment of opinions
COLING '04 Proceedings of the 20th international conference on Computational Linguistics
Recognizing contextual polarity in phrase-level sentiment analysis
HLT '05 Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing
A translation model for sentence retrieval
HLT '05 Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing
Topic sentiment mixture: modeling facets and opinions in weblogs
Proceedings of the 16th international conference on World Wide Web
ADC '07 Proceedings of the eighteenth conference on Australasian database - Volume 63
A generation model to unify topic relevance and lexicon-based sentiment for opinion retrieval
Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
Opinion Mining and Sentiment Analysis
Foundations and Trends in Information Retrieval
A relevance model for a data warehouse contextualized with documents
Information Processing and Management: an International Journal
Kinds of features for Chinese opinionated information retrieval
ACL '07 Proceedings of the 45th Annual Meeting of the ACL: Student Research Workshop
CLIAWS3 '09 Proceedings of the Third International Workshop on Cross Lingual Information Access: Addressing the Information Need of Multilingual Societies
Improving product review search experiences on general search engines
Proceedings of the 11th International Conference on Electronic Commerce
Using bilingual knowledge and ensemble techniques for unsupervised Chinese sentiment analysis
EMNLP '08 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Interactive clustering of text collections according to a user-specified criterion
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Joint sentiment/topic model for sentiment analysis
Proceedings of the 18th ACM conference on Information and knowledge management
A unified relevance model for opinion retrieval
Proceedings of the 18th ACM conference on Information and knowledge management
Locally contextualized smoothing of language models for sentiment sentence retrieval
Proceedings of the 1st international CIKM workshop on Topic-sentiment analysis for mass opinion
Domain Specific Opinion Retrieval
AIRS '09 Proceedings of the 5th Asia Information Retrieval Symposium on Information Retrieval Technology
PCM '09 Proceedings of the 10th Pacific Rim Conference on Multimedia: Advances in Multimedia Information Processing
Automatic construction of an opinion-term vocabulary for ad hoc retrieval
ECIR'08 Proceedings of the IR research, 30th European conference on Advances in information retrieval
Proximity-based opinion retrieval
Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval
Language-model-based pro/con classification of political text
Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval
On performance of topical opinion retrieval
Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval
A unified graph model for sentence-based opinion retrieval
ACL '10 Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics
Document sentiment classification by exploring description model of topical terms
Computer Speech and Language
Aspect and sentiment unification model for online review analysis
Proceedings of the fourth ACM international conference on Web search and data mining
Integrating web feed opinions into a corporate data warehouse
Proceedings of the 2nd International Workshop on Business intelligencE and the WEB
Preface to the 2nd international workshop on unstructured data management (USDM 2011)
APWeb'11 Proceedings of the 13th Asia-Pacific web conference on Web technologies and applications
APWeb'11 Proceedings of the 13th Asia-Pacific web conference on Web technologies and applications
Probabilistic ranking of product features from customer reviews
IbPRIA'11 Proceedings of the 5th Iberian conference on Pattern recognition and image analysis
Mining contrastive opinions on political texts using cross-perspective topic model
Proceedings of the fifth ACM international conference on Web search and data mining
Blog opinion retrieval based on topic-opinion mixture model
PAKDD'10 Proceedings of the 14th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining - Volume Part II
A domain independent framework to extract and aggregate analogous features in online reviews
CICLing'12 Proceedings of the 13th international conference on Computational Linguistics and Intelligent Text Processing - Volume Part I
Aggregation Methods for Proximity-Based Opinion Retrieval
ACM Transactions on Information Systems (TOIS)
Sentiment classification based on phonetic characteristics
ECIR'13 Proceedings of the 35th European conference on Advances in Information Retrieval
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Ranking documents or sentences according to both topic and sentiment relevance should serve a critical function in helping users when topics and sentiment polarities of the targeted text are not explicitly given, as is often the case on the web. In this paper, we propose several sentiment information retrieval models in the framework of probabilistic language models, assuming that a user both inputs query terms expressing a certain topic and also specifies a sentiment polarity of interest in some manner. We combine sentiment relevance models and topic relevance models with model parameters estimated from training data, considering the topic dependence of the sentiment. Our experiments prove that our models are effective.