On helmholtz's principle for documents processing
Proceedings of the 10th ACM symposium on Document engineering
Automatic sentiment analysis using the textual pattern content similarity in natural language
TSD'10 Proceedings of the 13th international conference on Text, speech and dialogue
Aspect and sentiment unification model for online review analysis
Proceedings of the fourth ACM international conference on Web search and data mining
Computational Linguistics
Architecture for a parallel focused crawler for clickstream analysis
ACIIDS'11 Proceedings of the Third international conference on Intelligent information and database systems - Volume Part I
Automatic keyphrase extraction by bridging vocabulary gap
CoNLL '11 Proceedings of the Fifteenth Conference on Computational Natural Language Learning
Mining the interests of Chinese microbloggers via keyword extraction
Frontiers of Computer Science in China
Large scale microblog mining using distributed MB-LDA
Proceedings of the 21st international conference companion on World Wide Web
Analyzing Online Review Helpfulness Using a Regressional ReliefF-Enhanced Text Mining Method
ACM Transactions on Management Information Systems (TMIS)
Understanding public-access cyberlearning projects using text mining and topic analysis
Journal of the American Society for Information Science and Technology
Regularized Latent Semantic Indexing: A New Approach to Large-Scale Topic Modeling
ACM Transactions on Information Systems (TOIS)
Construction of Chinese A-shares Network Using Latent Dirichlet Allocation
WI-IAT '12 Proceedings of the The 2012 IEEE/WIC/ACM International Joint Conferences on Web Intelligence and Intelligent Agent Technology - Volume 01
On Knowledge-Enhanced Document Clustering
International Journal of Information Retrieval Research
| Hi-index | 0.00 |
Giving a broad perspective of the field from numerous vantage points, Text Mining focuses on statistical methods for text mining and analysis. It examines methods to automatically cluster and classify text documents and applies these methods in a variety of areas, including adaptive information filtering, information distillation, and text search. The book begins with the classification of documents into predefined categories and then describes novel methods for clustering documents into groups that are not predefined. It concludes with various text mining applications that have significant implications for future research and industrial use.