Optimising Ontology Stream Reasoning with Truth Maintenance System

Yuan Ren; Jeff Z. Pan

doi:10.1145/2063576.2063696

Optimising Ontology Stream Reasoning with Truth Maintenance System

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract / Description of output

So far researchers in the Description Logics / Ontology communities mainly consider ontology reasoning services for static ontologies. The rapid development of the Semantic Web and its emerging data ask for reasoning technologies for dynamic knowledge streams. Existing work on stream reasoning is focused on lightweight languages such as RDF and RDFS. In this paper, we introduce the notion of Ontology Stream Management System (OSMS) and present a stream-reasoning approach based on Truth Maintenance System (TMS). We present optimised EL++ algorithm to reduce memory consumption. Our evaluations show that the optimisation improves TMS-enabled EL++ reasoning to deal with relatively large volumes of data and update efficiently.

Original language	English
Title of host publication	Proceedings of the 20th ACM International Conference on Information and Knowledge Management
Editors	Bettina Berendt, Arjen de Vries, Wenfei Fan, Craig MacDonald, Iadh Ounis, Ian Ruthven
Place of Publication	New York, NY, USA
Publisher	Association for Computing Machinery, Inc
Pages	831–836
Number of pages	6
ISBN (Print)	9781450307178
DOIs	https://doi.org/10.1145/2063576.2063696
Publication status	Published - 24 Oct 2011
Event	20th ACM Conference on Infromation and Knowledge Management - Glasgow, United Kingdom Duration: 24 Oct 2011 → 28 Oct 2011 Conference number: 20 http://www.cikm2011.org/index.html

Publication series

Name	CIKM '11
Publisher	Association for Computing Machinery

Conference

Conference	20th ACM Conference on Infromation and Knowledge Management
Abbreviated title	CIKM 2011
Country/Territory	United Kingdom
City	Glasgow
Period	24/10/11 → 28/10/11
Internet address	http://www.cikm2011.org/index.html

Keywords / Materials (for Non-textual outputs)

ontology
stream reasoning
truth maintenance system

Access to Document

10.1145/2063576.2063696Licence: All Rights Reserved

https://dl.acm.org/doi/abs/10.1145/2063576.2063696Licence: All Rights Reserved

Cite this

Ren, Y., & Pan, J. Z. (2011). Optimising Ontology Stream Reasoning with Truth Maintenance System. In B. Berendt, A. de Vries, W. Fan, C. MacDonald, I. Ounis, & I. Ruthven (Eds.), Proceedings of the 20th ACM International Conference on Information and Knowledge Management (pp. 831–836). (CIKM '11). Association for Computing Machinery, Inc. https://doi.org/10.1145/2063576.2063696

Ren, Yuan ; Pan, Jeff Z. / Optimising Ontology Stream Reasoning with Truth Maintenance System. Proceedings of the 20th ACM International Conference on Information and Knowledge Management. editor / Bettina Berendt ; Arjen de Vries ; Wenfei Fan ; Craig MacDonald ; Iadh Ounis ; Ian Ruthven. New York, NY, USA : Association for Computing Machinery, Inc, 2011. pp. 831–836 (CIKM '11).

@inproceedings{c2ca5688c51c453f9ef392e6563fbb90,

title = "Optimising Ontology Stream Reasoning with Truth Maintenance System",

abstract = "So far researchers in the Description Logics / Ontology communities mainly consider ontology reasoning services for static ontologies. The rapid development of the Semantic Web and its emerging data ask for reasoning technologies for dynamic knowledge streams. Existing work on stream reasoning is focused on lightweight languages such as RDF and RDFS. In this paper, we introduce the notion of Ontology Stream Management System (OSMS) and present a stream-reasoning approach based on Truth Maintenance System (TMS). We present optimised EL++ algorithm to reduce memory consumption. Our evaluations show that the optimisation improves TMS-enabled EL++ reasoning to deal with relatively large volumes of data and update efficiently.",

keywords = "ontology, stream reasoning, truth maintenance system",

author = "Yuan Ren and Pan, {Jeff Z.}",

year = "2011",

month = oct,

day = "24",

doi = "10.1145/2063576.2063696",

language = "English",

isbn = "9781450307178",

series = "CIKM '11",

publisher = "Association for Computing Machinery, Inc",

pages = "831–836",

editor = "Bettina Berendt and {de Vries}, Arjen and Wenfei Fan and Craig MacDonald and Iadh Ounis and Ian Ruthven",

booktitle = "Proceedings of the 20th ACM International Conference on Information and Knowledge Management",

note = "20th ACM Conference on Infromation and Knowledge Management, CIKM 2011 ; Conference date: 24-10-2011 Through 28-10-2011",

url = "http://www.cikm2011.org/index.html",

}

Ren, Y & Pan, JZ 2011, Optimising Ontology Stream Reasoning with Truth Maintenance System. in B Berendt, A de Vries, W Fan, C MacDonald, I Ounis & I Ruthven (eds), Proceedings of the 20th ACM International Conference on Information and Knowledge Management. CIKM '11, Association for Computing Machinery, Inc, New York, NY, USA, pp. 831–836, 20th ACM Conference on Infromation and Knowledge Management, Glasgow, United Kingdom, 24/10/11. https://doi.org/10.1145/2063576.2063696

Optimising Ontology Stream Reasoning with Truth Maintenance System. / Ren, Yuan; Pan, Jeff Z.
Proceedings of the 20th ACM International Conference on Information and Knowledge Management. ed. / Bettina Berendt; Arjen de Vries; Wenfei Fan; Craig MacDonald; Iadh Ounis; Ian Ruthven. New York, NY, USA: Association for Computing Machinery, Inc, 2011. p. 831–836 (CIKM '11).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - Optimising Ontology Stream Reasoning with Truth Maintenance System

AU - Ren, Yuan

AU - Pan, Jeff Z.

N1 - Conference code: 20

PY - 2011/10/24

Y1 - 2011/10/24

N2 - So far researchers in the Description Logics / Ontology communities mainly consider ontology reasoning services for static ontologies. The rapid development of the Semantic Web and its emerging data ask for reasoning technologies for dynamic knowledge streams. Existing work on stream reasoning is focused on lightweight languages such as RDF and RDFS. In this paper, we introduce the notion of Ontology Stream Management System (OSMS) and present a stream-reasoning approach based on Truth Maintenance System (TMS). We present optimised EL++ algorithm to reduce memory consumption. Our evaluations show that the optimisation improves TMS-enabled EL++ reasoning to deal with relatively large volumes of data and update efficiently.

AB - So far researchers in the Description Logics / Ontology communities mainly consider ontology reasoning services for static ontologies. The rapid development of the Semantic Web and its emerging data ask for reasoning technologies for dynamic knowledge streams. Existing work on stream reasoning is focused on lightweight languages such as RDF and RDFS. In this paper, we introduce the notion of Ontology Stream Management System (OSMS) and present a stream-reasoning approach based on Truth Maintenance System (TMS). We present optimised EL++ algorithm to reduce memory consumption. Our evaluations show that the optimisation improves TMS-enabled EL++ reasoning to deal with relatively large volumes of data and update efficiently.

KW - ontology

KW - stream reasoning

KW - truth maintenance system

U2 - 10.1145/2063576.2063696

DO - 10.1145/2063576.2063696

M3 - Conference contribution

SN - 9781450307178

T3 - CIKM '11

SP - 831

EP - 836

BT - Proceedings of the 20th ACM International Conference on Information and Knowledge Management

A2 - Berendt, Bettina

A2 - de Vries, Arjen

A2 - Fan, Wenfei

A2 - MacDonald, Craig

A2 - Ounis, Iadh

A2 - Ruthven, Ian

PB - Association for Computing Machinery, Inc

CY - New York, NY, USA

T2 - 20th ACM Conference on Infromation and Knowledge Management

Y2 - 24 October 2011 through 28 October 2011

ER -

Ren Y, Pan JZ. Optimising Ontology Stream Reasoning with Truth Maintenance System. In Berendt B, de Vries A, Fan W, MacDonald C, Ounis I, Ruthven I, editors, Proceedings of the 20th ACM International Conference on Information and Knowledge Management. New York, NY, USA: Association for Computing Machinery, Inc. 2011. p. 831–836. (CIKM '11). doi: 10.1145/2063576.2063696

Optimising Ontology Stream Reasoning with Truth Maintenance System

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Keywords / Materials (for Non-textual outputs)

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