Introduction to algorithms
Computational Intelligence
Exact and approximate reasoning about temporal relations
Computational Intelligence
An episodic knowledge representation for narrative texts
Proceedings of the first international conference on Principles of knowledge representation and reasoning
Artificial Intelligence - Special issue on knowledge representation
Effective solution of qualitative interval constraint problems
Artificial Intelligence
Journal of the ACM (JACM)
Maintaining knowledge about temporal intervals
Communications of the ACM
Performance of Temporal Reasoning Systems
Performance of Temporal Reasoning Systems
ACM SIGART Bulletin
Querying Temporal Constraint Networks: A Unifying Approach
Applied Intelligence
Towards a complete classification of tractability in Allen's algebra
IJCAI'97 Proceedings of the Fifteenth international joint conference on Artifical intelligence - Volume 2
Eight maximal tractable subclasses of Allen's algebra with metric time
Journal of Artificial Intelligence Research
A linear-programming approach to temporal reasoning
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 2
Maximal tractable subclasses of Allen's interval algebra: preliminary report
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 1
Avian influenza: Temporal modeling of a human to human transmission case
Expert Systems with Applications: An International Journal
Temporal representation and reasoning in artificial intelligence: A review
Mathematical and Computer Modelling: An International Journal
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We describe two temporal reasoning systems called Timegraph I and II, which can efficiently manage large sets of relations in the Point Algebra as well as metric information. Our representation is based on timegraphs, graphs partitioned into a set of chains on which the search is supported by a metagraph data structure. Timegraph I was originally developed by Taugher, Schubert and Miller in the context of story comprehension. Timegraph II provides useful extensions which makes the system more expressive in the representation of qualitative information and suitable for a larger class of applications. Experimental results show that our approach is very efficient, especially when the given relations admit representation as a collection of chains connected by relatively few cross-chain links.