BoosTexter: A Boosting-based Systemfor Text Categorization
Machine Learning - Special issue on 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
Event threading within news topics
Proceedings of the thirteenth ACM international conference on Information and knowledge management
Scalable hierarchical topic detection: exploring a sample based approach
Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
NewsInEssence: summarizing online news topics
Communications of the ACM - The digital society
Tracking and summarizing news on a daily basis with Columbia's Newsblaster
HLT '02 Proceedings of the second international conference on Human Language Technology Research
Incident threading for news passages
Proceedings of the 18th ACM conference on Information and knowledge management
Bipolar person name identification of topic documents using principal component analysis
COLING '10 Proceedings of the 23rd International Conference on Computational Linguistics
An incremental method for causal network construction
WAIM'10 Proceedings of the 11th international conference on Web-age information management
Topic chains for understanding a news corpus
CICLing'11 Proceedings of the 12th international conference on Computational linguistics and intelligent text processing - Volume Part II
Event detection with spatial latent Dirichlet allocation
Proceedings of the 11th annual international ACM/IEEE joint conference on Digital libraries
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
Mining event temporal boundaries from news corpora through evolution phase discovery
WAIM'11 Proceedings of the 12th international conference on Web-age information management
A model-based EM method for topic person name multi-polarization
AIRS'11 Proceedings of the 7th Asia conference on Information Retrieval Technology
A preference learning approach to sentence ordering for multi-document summarization
Information Sciences: an International Journal
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News reports are being produced and disseminated in overwhelming volume, making it difficult to keep up with the newest information. Most previous research in automatic news organization treated news topics as a flat list, ignoring the intrinsic connection among individual reports. We argue that more contextual information within and across the topics will benefit users in their news understanding process. A news organization infrastructure, incident threading, is proposed in this article. All text snippets describing the occurrence of a real-world happening are combined into a news incident, and a network is composed of incidents that are interconnected by links in certain types. A limited vocabulary of connection types is defined and corresponding rules are established based upon the human experience of news understanding. The incident threading system is implemented with two different algorithms. One starts from clustering of text passages and then creates links with pre-built rules. The other method defines a global score function over the whole collection and solves the optimization problem with simulated annealing. The former achieves higher accuracy in the identification of incidents and the latter generates better links, which is preferred since the links are more important for the formation of the incident network.