This paper proposes and evaluates a distributed, parallel approach for reasoning over large scale datasets using Allen's Interval Algebra (IA). We have developed and implemented algorithms that reason over IA networks using the Spark distributed processing framework. Experiments have been conducted by deploying the algorithms on computer clusters using synthetic datasets with various characteristics. We show that reasoning over datasets consisting of millions of interval relations is feasible and that our implementation scales effectively. The size of the IA networks we are able to reason over is far greater than those found in previously published works.
|Title of host publication||Advances in Soft Computing|
|Subtitle of host publication||15th Mexican International Conference on Artificial Intelligence, MICAI 2016, Cancún, Mexico, October 23–28, 2016, Proceedings, Part II|
|Editors||Obdulia Pichardo-Lagunas, Sabino Miranda-Jiménez|
|Number of pages||13|
|Publication status||Published - 2 Aug 2017|
|Event||Mexican International Conference on Artificial Intelligence - Cancun, Mexico|
Duration: 23 Oct 2016 → 29 Oct 2016
Conference number: 15
http://www.micai.org/2016/ (Link to Conference Website)
|Name||Lecture Notes in Computer Science|
|Conference||Mexican International Conference on Artificial Intelligence|
|Period||23/10/16 → 29/10/16|
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- Department of Computer Science - Senior Lecturer
- Centre for Planning, Autonomy and Representation of Knowledge