Authoritative sources in a hyperlinked environment
Journal of the ACM (JACM)
Generic text summarization using relevance measure and latent semantic analysis
Proceedings of the 24th annual international ACM SIGIR conference on Research and development in information retrieval
Measuring praise and criticism: Inference of semantic orientation from association
ACM Transactions on Information Systems (TOIS)
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
Event threading within news topics
Proceedings of the thirteenth ACM international conference on Information and knowledge management
Finding and linking incidents in news
Proceedings of the sixteenth ACM conference on Conference on information and knowledge management
TSCAN: a novel method for topic summarization and content anatomy
Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
Introduction to Information Retrieval
Introduction to Information Retrieval
Mining opinions in comparative sentences
COLING '08 Proceedings of the 22nd International Conference on Computational Linguistics - Volume 1
Fully automatic lexicon expansion for domain-oriented sentiment analysis
EMNLP '06 Proceedings of the 2006 Conference on Empirical Methods in Natural Language Processing
A model-based EM method for topic person name multi-polarization
AIRS'11 Proceedings of the 7th Asia conference on Information Retrieval Technology
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In this paper, we propose an unsupervised approach for identifying bipolar person names in a set of topic documents. We employ principal component analysis (PCA) to discover bipolar word usage patterns of person names in the documents and show that the signs of the entries in the principal eigenvector of PCA partition the person names into bipolar groups spontaneously. Empirical evaluations demonstrate the efficacy of the proposed approach in identifying bipolar person names of topics.