Document language models, query models, and risk minimization for information retrieval
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 information retrieval
ACM Transactions on Information Systems (TOIS)
Learning extraction patterns for subjective expressions
EMNLP '03 Proceedings of the 2003 conference on Empirical methods in natural language processing
Identifying and analyzing judgment opinions
HLT-NAACL '06 Proceedings of the main conference on Human Language Technology Conference of the North American Chapter of the Association of Computational Linguistics
COLING-ACL '06 Proceedings of the COLING/ACL on Main conference poster sessions
Introduction to the NTCIR-6 Special Issue
ACM Transactions on Asian Language Information Processing (TALIP)
Automatic seed word selection for unsupervised sentiment classification of Chinese text
COLING '08 Proceedings of the 22nd International Conference on Computational Linguistics - Volume 1
Multilingual subjectivity analysis using machine translation
EMNLP '08 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Extracting opinions, opinion holders, and topics expressed in online news media text
SST '06 Proceedings of the Workshop on Sentiment and Subjectivity in Text
Proximity-based opinion retrieval
Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval
Application of semi-supervised learning to evaluative expression classification
CICLing'06 Proceedings of the 7th international conference on Computational Linguistics and Intelligent Text Processing
A new method for sentiment classification in text retrieval
IJCNLP'05 Proceedings of the Second international joint conference on Natural Language Processing
| Hi-index | 0.00 |
We wish to address the challenging task of opinion mining about organizations, people and places from different languages. It is known that resources and tools for mining opinions are scarce. In our study, we leverage comparable news articles collection to retrieve opinions about people (opinion targets) in resource scarce language like Hindi. Opinions expressed about opinion targets (Named Entities)given by adjectives and verbs known as opinion words are extracted from English collection of comparable corpora to get transliterated and translated to resource scare languages. Transformed opinion words are then used to create subjective language model (SLM) and structured opinion queries (OQs) using inference network (IN) for retrieval to confirm the opinion about opinion targets in documents. Experiments have shown that OQs and SLM with IN framework are effective for opinion mining tasks in minimal resource languages when compared to other retrieval approaches.