An algorithm for suffix stripping
Readings in information retrieval
Fast Algorithms for Mining Association Rules in Large Databases
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
REES: a large-scale relation and event extraction system
ANLC '00 Proceedings of the sixth conference on Applied natural language processing
Inferring temporal ordering of events in news
NAACL-Short '03 Proceedings of the 2003 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology: companion volume of the Proceedings of HLT-NAACL 2003--short papers - Volume 2
Robust temporal processing of news
ACL '00 Proceedings of the 38th Annual Meeting on Association for Computational Linguistics
From temporal expressions to temporal information: semantic tagging of news messages
TASIP '01 Proceedings of the workshop on Temporal and spatial information processing - Volume 13
Assigning time-stamps to event-clauses
TASIP '01 Proceedings of the workshop on Temporal and spatial information processing - Volume 13
Automating temporal annotation with TARSQI
ACLdemo '05 Proceedings of the ACL 2005 on Interactive poster and demonstration sessions
Timestamp evidence correlation by model based clock hypothesis testing
Proceedings of the 1st international conference on Forensic applications and techniques in telecommunications, information, and multimedia and workshop
Temporal processing with the TARSQI toolkit
COLING '08 22nd International Conference on on Computational Linguistics: Demonstration Papers
An approach for temporal analysis of email data based on segmentation
Data & Knowledge Engineering
Drawing TimeML relations with TBox
Proceedings of the 2005 international conference on Annotating, extracting and reasoning about time and events
Tense interpretation in the context of narrative
AAAI'91 Proceedings of the ninth National conference on Artificial intelligence - Volume 1
Towards an integrated e-mail forensic analysis framework
Digital Investigation: The International Journal of Digital Forensics & Incident Response
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In criminal investigation and criminal justice, investigators are usually faced with several reports, which contain a set of events of interest. Often, it is important to be able to order these events so that relevant queries can be posed on this ordering, such as "was X at location Y when the murder took place?". However, ordering of these events is very difficult, especially if very few events are anchored in time, i.e., few events are associated with an explicit time. Manual extraction of all the events of interest from these reports is tedious. On the other hand, automated extraction is inaccurate at best, in the sense that either several events that may not be important could be included. This ultimately gives a large set of events to consider, and imposing an ordering on this set can yield a large tree structure, where nodes represent an event of interest, and an edge (i, j) indicates that event i occurred before or at the same time as event j, and the root node represents a special "start" event. In this paper, we investigate two techniques for automating extraction of events, and then ordering these. We compare the efficiency of the techniques through the size of the tree structure obtained