This Article 
   
 Share 
   
 Bibliographic References 
   
 Add to: 
 
Digg
Furl
Spurl
Blink
Simpy
Google
Del.icio.us
Y!MyWeb
 
 Search 
   
Linear Temporal Sequences and Their Interpretation Using Midpoint Relationships
January 2005 (vol. 17 no. 1)
pp. 133-135
The temporal interval relationships formalized by Allen, and later extended to accommodate semi-intervals by Freksa, have been widely utilized in both data modeling and artificial intelligence research to facilitate reasoning between the relative temporal ordering of events. In practice, however, some modifications to the relationships are necessary when linear temporal sequences are provided, when event times are aggregated, or when data is supplied to a granularity which is larger than required. This paper discusses these modifications and outlines a solution to this problem which accommodates any available knowledge of interval midpoints.

[1] J.F. Allen, “Maintaining Knowledge About Temporal Intervals,” Comm. ACM, vol. 26, no. 11, pp. 832-843, 1983.
[2] P.B. Ladkin, “Models of Axioms for Time Intervals,” Proc. Sixth Nat'l Conf. ArtificialIntelligence (AAAI '87), pp. 234-239, 1987.
[3] R. Gennari, “Temporal Reasoning and Constraint Programming–A Survey,” CWI Quarterly, vol. 11, nos. 2/3, pp. 163-214, 1998.
[4] L. Vila, “A Survey on Temporal Reasoning in Artificial Intelligence,” Artificial Intelligence Comm., vol. 7, no. 1, pp. 4-28, 1994.
[5] C. Freksa, “Temporal Reasoning Based on Semi-Intervals,” Artificial Intelligence, vol. 54, pp. 199-227, 1992.
[6] M.B. Vilain, “A System for Reasoning About Time,” Proc. Nat'l Conf. Artificial Intelligence (AAAI '82), pp. 197-201, 1982.
[7] C. Mooney and J.F. Roddick, “Mining Relationships Between Interacting Episodes,” Proc. 2004 SIAM Int'l Conf. Data Mining, U. Dayal and M.W. Berry, eds., 2004.
[8] J.F. Allen, “An Interval-Based Representation of Temporal Knowledge,” Proc. Seventh Int'l Joint Conf. Artificial Intelligence, A. Drinan, ed., pp. 221-226, 1981.
[9] J.F. Allen, “Towards a General Theory of Action and Time,” Artificial Intelligence, vol. 23, no. 2, pp. 123-154, 1984.
[10] J.F. Allen and P.J. Hayes, “Moments and Points in an Interval-Based Temporal Logic,” Computational Intelligence, vol. 5, pp. 225-238, 1989.

Index Terms:
Temporal reasoning, temporal uncertainty, Allen temporal relationships, Freksa semi-intervals.
Citation:
John F. Roddick, Carl H. Mooney, "Linear Temporal Sequences and Their Interpretation Using Midpoint Relationships," IEEE Transactions on Knowledge and Data Engineering, vol. 17, no. 1, pp. 133-135, Jan. 2005, doi:10.1109/TKDE.2005.12
Usage of this product signifies your acceptance of the Terms of Use.