Elements of information theory
Elements of information theory
Viewing morphology as an inference process
SIGIR '93 Proceedings of the 16th annual international ACM SIGIR conference on Research and development in information retrieval
A study of retrospective and on-line event detection
Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval
BoosTexter: A Boosting-based Systemfor Text Categorization
Machine Learning - Special issue on information retrieval
Combining semantic and syntactic document classifiers to improve first story detection
Proceedings of the 24th annual international ACM SIGIR conference on Research and development in information retrieval
Topic Detection and Tracking: Event-Based Information Organization
Topic Detection and Tracking: Event-Based Information Organization
Learning Approaches for Detecting and Tracking News Events
IEEE Intelligent Systems
A Comparative Study on Feature Selection in Text Categorization
ICML '97 Proceedings of the Fourteenth International Conference on Machine Learning
Topic-conditioned novelty detection
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
A System for new event detection
Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval
On-Line New Event Detection using Single Pass Clustering TITLE2:
On-Line New Event Detection using Single Pass Clustering TITLE2:
Simple Semantics in Topic Detection and Tracking
Information Retrieval
Text classification and named entities for new event detection
Proceedings of the 27th annual international ACM SIGIR conference on Research and development in information retrieval
Using names and topics for new event detection
HLT '05 Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing
Automatic online news issue construction in web environment
Proceedings of the 17th international conference on World Wide Web
Automatic online news topic ranking using media focus and user attention based on aging theory
Proceedings of the 17th ACM conference on Information and knowledge management
Event detection with common user interests
Proceedings of the 10th ACM workshop on Web information and data management
Topic Detection and Tracking for Threaded Discussion Communities
WI-IAT '08 Proceedings of the 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Volume 01
An Automatic Online News Topic Keyphrase Extraction System
WI-IAT '08 Proceedings of the 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Volume 01
Discovering event episodes from news corpora: a temporal-based approach
Proceedings of the 11th International Conference on Electronic Commerce
Online New Event Detection Based on IPLSA
ADMA '09 Proceedings of the 5th International Conference on Advanced Data Mining and Applications
Cross-language linking of news stories on the web using interlingual topic modelling
Proceedings of the 2nd ACM workshop on Social web search and mining
Bursty topics extraction for web forums
Proceedings of the eleventh international workshop on Web information and data management
Learning similarity metrics for event identification in social media
Proceedings of the third ACM international conference on Web search and data mining
Tell me more, not just "more of the same"
Proceedings of the 15th international conference on Intelligent user interfaces
New event detection and topic tracking in Turkish
Journal of the American Society for Information Science and Technology
A comparison of named entity patterns from a user analysis and a system analysis
ECIR'08 Proceedings of the IR research, 30th European conference on Advances in information retrieval
Mining the blogosphere for top news stories identification
Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval
Evolutionary timeline summarization: a balanced optimization framework via iterative substitution
Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval
An event-centric model for multilingual document similarity
Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval
Identifying content for planned events across social media sites
Proceedings of the fifth ACM international conference on Web search and data mining
Predicting the future impact of news events
ECIR'12 Proceedings of the 34th European conference on Advances in Information Retrieval
Evaluation of an interactive topic detection and tracking interface
Journal of Information Science
Comparative document summarization via discriminative sentence selection
ACM Transactions on Knowledge Discovery from Data (TKDD)
Ranking news events by influence decay and information fusion for media and users
Proceedings of the 21st ACM international conference on Information and knowledge management
Representations for multi-document event clustering
Data Mining and Knowledge Discovery
Comparative Document Summarization via Discriminative Sentence Selection
ACM Transactions on Knowledge Discovery from Data (TKDD)
Term Weighting Schemes for Emerging Event Detection
WI-IAT '12 Proceedings of the The 2012 IEEE/WIC/ACM International Joint Conferences on Web Intelligence and Intelligent Agent Technology - Volume 01
Event identification in web social media through named entity recognition and topic modeling
Data & Knowledge Engineering
Hi-index | 0.00 |
New Event Detection (NED) aims at detecting from one or multiple streams of news stories that which one is reported on a new event (i.e. not reported previously). With the overwhelming volume of news available today, there is an increasing need for a NED system which is able to detect new events more efficiently and accurately. In this paper we propose a new NED model to speed up the NED task by using news indexing-tree dynamically. Moreover, based on the observation that terms of different types have different effects for NED task, two term reweighting approaches are proposed to improve NED accuracy. In the first approach, we propose to adjust term weights dynamically based on previous story clusters and in the second approach, we propose to employ statistics on training data to learn the named entity reweighting model for each class of stories. Experimental results on two Linguistic Data Consortium (LDC) datasets TDT2 and TDT3 show that the proposed model can improve both efficiency and accuracy of NED task significantly, compared to the baseline system and other existing systems.