Foundations of statistical natural language processing
Foundations of statistical natural language processing
Improving text categorization methods for event tracking
SIGIR '00 Proceedings of the 23rd annual international ACM SIGIR conference on Research and development in information retrieval
Topic segmentation with an aspect hidden Markov model
Proceedings of the 24th annual international ACM SIGIR conference on Research and development in information retrieval
Machine Learning
Extended models and tools for high-performance part-of-speech tagger
COLING '00 Proceedings of the 18th conference on Computational linguistics - Volume 1
Investigations on event evolution in TDT
NAACLstudent '03 Proceedings of the 2003 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology: Proceedings of the HLT-NAACL 2003 student research workshop - Volume 3
COLING-ACL '06 Proceedings of the COLING/ACL on Main conference poster sessions
Topics Identification Based on Event Sequence Using Co-occurrence Words
NLDB '08 Proceedings of the 13th international conference on Natural Language and Information Systems: Applications of Natural Language to Information Systems
Data Stream Prediction Using Incremental Hidden Markov Models
DaWaK '09 Proceedings of the 11th International Conference on Data Warehousing and Knowledge Discovery
| Hi-index | 0.00 |
In this paper, we propose a sophisticated technique for classification of topics appeared in documents. There have been many investigation proposed so far, but few investigation which capture contents directly. Here we consider a topics as a sequence of events and a classification problem as segmentation (or tagging) problem based on Hidden Markov Model (HMM). We show some experimental results to see the validity of the method.