On-line new event detection and tracking
Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval
Extracting significant time varying features from text
Proceedings of the eighth international conference on Information and knowledge management
Information Extraction: Techniques and Challenges
SCIE '97 International Summer School on Information Extraction: A Multidisciplinary Approach to an Emerging Information Technology
Retrieval of Information from Temporal Document Databases
Proceedings of the Workshop on Object-Oriented Technology
A Retrieval Language for Historical Documents
DEXA '98 Proceedings of the 9th International Conference on Database and Expert Systems Applications
Time frames: temporal augmentation of the news
IBM Systems Journal
Detecting Events and Topics by Using Temporal References
IBERAMIA 2002 Proceedings of the 8th Ibero-American Conference on AI: Advances in Artificial Intelligence
Techniques and Tools for the Temporal Analysis of Retrieved Information
DEXA '01 Proceedings of the 12th International Conference on Database and Expert Systems Applications
Assessing context for age-related Spanish temporal phrases
AICS'09 Proceedings of the 20th Irish conference on Artificial intelligence and cognitive science
Labeling documents with timestamps: learning from their time expressions
ACL '12 Proceedings of the 50th Annual Meeting of the Association for Computational Linguistics: Long Papers - Volume 1
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This paper presents a new approach for the automatic assignment of document event-time periods. This approach consists of extracting temporal information from document texts, and translating it into temporal expressions of a formal time model. From these expressions, we are able to approximately calculate the event-time periods of documents. The obtained event-time periods can be useful for both retrieving documents and finding relationships between them, and their inclusion in Information Retrieval Systems can produce significant improvements in their retrieval effectiveness.