Journal of the American Society for Information Science - Special topic issue on the history of documentation and information science: part II
A probabilistic model for retrospective news event detection
Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
Incorporating non-local information into information extraction systems by Gibbs sampling
ACL '05 Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics
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
Identifying Event Impacts by Monitoring the News Media
IV '08 Proceedings of the 2008 12th International Conference Information Visualisation
Event detection with common user interests
Proceedings of the 10th ACM workshop on Web information and data management
Predicting News Story Importance Using Language Features
WI-IAT '08 Proceedings of the 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Volume 01
Integration of news content into web results
Proceedings of the Second ACM International Conference on Web Search and Data Mining
Ranking and classifying attractiveness of photos in folksonomies
Proceedings of the 18th international conference on World wide web
Predicting the volume of comments on online news stories
Proceedings of the 18th ACM conference on Information and knowledge management
PET: a statistical model for popular events tracking in social communities
Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining
Proceedings of the 3rd International Semantic Search Workshop
Unsupervised public health event detection for epidemic intelligence
CIKM '10 Proceedings of the 19th ACM international conference on Information and knowledge management
Improvements to the SMO algorithm for SVM regression
IEEE Transactions on Neural Networks
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The amount of news content on the Web is increasing, enabling users to access news articles coming from a variety of sources: from newswires, news agencies, blogs, and at various places, e.g. even within Web search engines result pages. Anyhow, it still is a challenge for current search engines to decide which news events are worth being shown to the user (either for a newsworthy query or in a news portal). In this paper we define the task of predicting the future impact of news events. Being able to predict event impact will, for example, enable a newspaper to decide whether to follow a specific event or not, or a news search engine which stories to display. We define a flexible framework that, given some definition of impact, can predict its future development at the beginning of the event. We evaluate several possible definitions of event impact and experimentally identify the best features for each of them.