Large Scale Reasoning Using Allen's Interval Algebra

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

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.
Original languageEnglish
Title of host publicationAdvances in Soft Computing
Subtitle of host publication15th Mexican International Conference on Artificial Intelligence, MICAI 2016, Cancún, Mexico, October 23–28, 2016, Proceedings, Part II
EditorsObdulia Pichardo-Lagunas, Sabino Miranda-Jiménez
PublisherSpringer, Cham
Pages29-41
Number of pages13
ISBN (Electronic)9783319624280
ISBN (Print) 9783319624273
DOIs
Publication statusPublished - 2 Aug 2017
EventMexican International Conference on Artificial Intelligence - Cancun, Mexico
Duration: 23 Oct 201629 Oct 2016
Conference number: 15
http://www.micai.org/2016/ (Link to Conference Website)

Publication series

NameLecture Notes in Computer Science
PublisherSpringer
Volume10062
ISSN (Print)0302-9743

Conference

ConferenceMexican International Conference on Artificial Intelligence
Abbreviated titleMCIAI
CountryMexico
CityCancun
Period23/10/1629/10/16
Internet address

Fingerprint

Algebra
Electric sparks
Processing
Experiments

Cite this

Mantle, M., Batsakis, S., & Antoniou, G. (2017). Large Scale Reasoning Using Allen's Interval Algebra. In O. Pichardo-Lagunas, & S. Miranda-Jiménez (Eds.), Advances in Soft Computing: 15th Mexican International Conference on Artificial Intelligence, MICAI 2016, Cancún, Mexico, October 23–28, 2016, Proceedings, Part II (pp. 29-41). (Lecture Notes in Computer Science; Vol. 10062). Springer, Cham. https://doi.org/10.1007/978-3-319-62428-0_3
Mantle, Matthew ; Batsakis, Sotirios ; Antoniou, Grigoris. / Large Scale Reasoning Using Allen's Interval Algebra. Advances in Soft Computing: 15th Mexican International Conference on Artificial Intelligence, MICAI 2016, Cancún, Mexico, October 23–28, 2016, Proceedings, Part II. editor / Obdulia Pichardo-Lagunas ; Sabino Miranda-Jiménez. Springer, Cham, 2017. pp. 29-41 (Lecture Notes in Computer Science).
@inproceedings{9e7366f6048b4f31b162d18ba8812c53,
title = "Large Scale Reasoning Using Allen's Interval Algebra",
abstract = "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.",
keywords = "Distributed computing, MapReduce, Qualitative temporal reasoning",
author = "Matthew Mantle and Sotirios Batsakis and Grigoris Antoniou",
year = "2017",
month = "8",
day = "2",
doi = "10.1007/978-3-319-62428-0_3",
language = "English",
isbn = "9783319624273",
series = "Lecture Notes in Computer Science",
publisher = "Springer, Cham",
pages = "29--41",
editor = "Obdulia Pichardo-Lagunas and Sabino Miranda-Jim{\'e}nez",
booktitle = "Advances in Soft Computing",

}

Mantle, M, Batsakis, S & Antoniou, G 2017, Large Scale Reasoning Using Allen's Interval Algebra. in O Pichardo-Lagunas & S Miranda-Jiménez (eds), Advances in Soft Computing: 15th Mexican International Conference on Artificial Intelligence, MICAI 2016, Cancún, Mexico, October 23–28, 2016, Proceedings, Part II. Lecture Notes in Computer Science, vol. 10062, Springer, Cham, pp. 29-41, Mexican International Conference on Artificial Intelligence, Cancun, Mexico, 23/10/16. https://doi.org/10.1007/978-3-319-62428-0_3

Large Scale Reasoning Using Allen's Interval Algebra. / Mantle, Matthew; Batsakis, Sotirios; Antoniou, Grigoris.

Advances in Soft Computing: 15th Mexican International Conference on Artificial Intelligence, MICAI 2016, Cancún, Mexico, October 23–28, 2016, Proceedings, Part II. ed. / Obdulia Pichardo-Lagunas; Sabino Miranda-Jiménez. Springer, Cham, 2017. p. 29-41 (Lecture Notes in Computer Science; Vol. 10062).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

TY - GEN

T1 - Large Scale Reasoning Using Allen's Interval Algebra

AU - Mantle, Matthew

AU - Batsakis, Sotirios

AU - Antoniou, Grigoris

PY - 2017/8/2

Y1 - 2017/8/2

N2 - 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.

AB - 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.

KW - Distributed computing

KW - MapReduce

KW - Qualitative temporal reasoning

U2 - 10.1007/978-3-319-62428-0_3

DO - 10.1007/978-3-319-62428-0_3

M3 - Conference contribution

SN - 9783319624273

T3 - Lecture Notes in Computer Science

SP - 29

EP - 41

BT - Advances in Soft Computing

A2 - Pichardo-Lagunas, Obdulia

A2 - Miranda-Jiménez, Sabino

PB - Springer, Cham

ER -

Mantle M, Batsakis S, Antoniou G. Large Scale Reasoning Using Allen's Interval Algebra. In Pichardo-Lagunas O, Miranda-Jiménez S, editors, Advances in Soft Computing: 15th Mexican International Conference on Artificial Intelligence, MICAI 2016, Cancún, Mexico, October 23–28, 2016, Proceedings, Part II. Springer, Cham. 2017. p. 29-41. (Lecture Notes in Computer Science). https://doi.org/10.1007/978-3-319-62428-0_3