The nature of statistical learning theory
The nature of statistical learning theory
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
An Algorithm that Learns What‘s in a Name
Machine Learning - Special issue on natural language learning
First story detection in TDT is hard
Proceedings of the ninth international conference on Information and knowledge management
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
A Tutorial on Support Vector Machines for Pattern Recognition
Data Mining and Knowledge Discovery
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
Feature selection using linear classifier weights: interaction with classification models
Proceedings of the 27th annual international ACM SIGIR conference on Research and development in 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
Optimizing story link detection is not equivalent to optimizing new event detection
ACL '03 Proceedings of the 41st Annual Meeting on Association for Computational Linguistics - Volume 1
Automatic new topic identification using multiple linear regression
Information Processing and Management: an International Journal
New event detection based on indexing-tree and named entity
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
Relation Discovery from Thai News Articles Using Association Rule Mining
PAISI '09 Proceedings of the Pacific Asia Workshop on Intelligence and Security Informatics
Discovering event episodes from news corpora: a temporal-based approach
Proceedings of the 11th International Conference on Electronic Commerce
Novelty detection in patient histories: experiments with measures based on text compression
IDA'07 Proceedings of the 7th international conference on Intelligent data analysis
Using paraphrases for improving first story detection in news and Twitter
NAACL HLT '12 Proceedings of the 2012 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
Detecting and Tracking Topics and Events from Web Search Logs
ACM Transactions on Information Systems (TOIS)
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New Event Detection (NED) involves monitoring chronologically-ordered news streams to automatically detect the stories that report on new events. We compare two stories by finding three cosine similarities based on names, topics and the full text. These additional comparisons suggest treating the NED problem as a binary classification problem with the comparison scores serving as features. The classifier models we learned show statistically significant improvement over the baseline vector space model system on all the collections we tested, including the latest TDT5 collection.The presence of automatic speech recognizer (ASR) output of broadcast news in news streams can reduce performance and render our named entity recognition based approaches ineffective. We provide a solution to this problem achieving statistically significant improvements.