Automatic generation of overview timelines
SIGIR '00 Proceedings of the 23rd annual international ACM SIGIR conference on Research and development in information retrieval
Detecting and Browsing Events in Unstructured text
SIGIR '02 Proceedings of the 25th annual international ACM SIGIR conference on Research and development in information retrieval
Query based event extraction along a timeline
Proceedings of the 27th annual international ACM SIGIR conference on Research and development in information retrieval
Robust temporal processing of news
ACL '00 Proceedings of the 38th Annual Meeting on Association for Computational Linguistics
Assigning time-stamps to event-clauses
TASIP '01 Proceedings of the workshop on Temporal and spatial information processing - Volume 13
Towards automatic extraction of event and place semantics from flickr tags
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
On the value of temporal information in information retrieval
ACM SIGIR Forum
Temporal reasoning about fuzzy intervals
Artificial Intelligence
Learning sentence-internal temporal relations
Journal of Artificial Intelligence Research
TimeML-compliant text analysis for temporal reasoning
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
Temporal context representation and reasoning
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
Fuzzifying Allen's Temporal Interval Relations
IEEE Transactions on Fuzzy Systems
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Many real-world information needs are naturally formulated as queries with temporal constraints. However, the structured temporal background information needed to support such constraints is usually not available to information retrieval systems. As an alternative, we automatically compile temporal knowledge bases from web documents, combining whatever quantitative and qualitative temporal information we can find about events of interest. By using simple heuristic techniques for temporal information extraction, we initially focus more on recall than on precision, relying on the subsequent application of a fuzzy temporal reasoner to improve the reliability of the extracted information.