Probabilistic models for topic detection and tracking
ICASSP '99 Proceedings of the Acoustics, Speech, and Signal Processing, 1999. on 1999 IEEE International Conference - Volume 01
Overview and semantic issues of text mining
ACM SIGMOD Record
Topic Detection and Tracking for Chinese News Web Pages
ALPIT '08 Proceedings of the 2008 International Conference on Advanced Language Processing and Web Information Technology
News Keyword Extraction for Topic Tracking
NCM '08 Proceedings of the 2008 Fourth International Conference on Networked Computing and Advanced Information Management - Volume 02
Improving the Performance of Topic Tracking System by Ensemble
CSSE '08 Proceedings of the 2008 International Conference on Computer Science and Software Engineering - Volume 04
Use of NER Information for Improved Topic Tracking
ISDA '08 Proceedings of the 2008 Eighth International Conference on Intelligent Systems Design and Applications - Volume 03
Tracking Topic Evolution in News Environments
CECANDEEE '08 Proceedings of the 2008 10th IEEE Conference on E-Commerce Technology and the Fifth IEEE Conference on Enterprise Computing, E-Commerce and E-Services
A Dual-Center Event Description Model Used in Event Tracking
CSIE '09 Proceedings of the 2009 WRI World Congress on Computer Science and Information Engineering - Volume 04
An Effective Algorithm of News Topic Tracking
GCIS '09 Proceedings of the 2009 WRI Global Congress on Intelligent Systems - Volume 03
Applying an Enhanced Algorithm for Mining Incremental Updates on an Egyptian Newspaper Website
NCM '09 Proceedings of the 2009 Fifth International Joint Conference on INC, IMS and IDC
Subtopic Based Topic Evolution Analysis
WISM '09 Proceedings of the 2009 International Conference on Web Information Systems and Mining
| Hi-index | 0.00 |
Text mining is a field that automatically extracts previously unknown and useful information from unstructured textual data. It has strong connections with natural language processing. NLP has produced technologies that teach computers natural language so that they may analyze, understand and even generate text. Topic tracking is one of the technologies that has been developed and can be used in the text mining process. The main purpose of topic tracking is to identify and follow events presented in multiple news sources, including newswires, radio and TV broadcasts. It collects dispersed information together and makes it easy for user to get a general understanding. In this paper, a survey of recent topic tracking techniques is presented.