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Authors: A. Aldeeb ; D. M. Pearce ; K. Crockett and M. J. Stanton

Affiliation: Manchester Metropolitan University, United Kingdom

ISBN: 978-989-8425-05-8

Keyword(s): Workflow management system, exception handling, case-based reasoning, sentence similarity measures

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Artificial Intelligence and Decision Support Systems ; Biomedical Engineering ; Case-Based Reasoning ; Data Engineering ; Enterprise Information Systems ; Group Decision Support Systems ; Health Information Systems ; Industrial Applications of Artificial Intelligence ; Informatics in Control, Automation and Robotics ; Information Systems Analysis and Specification ; Intelligent Control Systems and Optimization ; Knowledge Engineering ; Knowledge Engineering and Ontology Development ; Knowledge Management ; Knowledge-Based Systems ; Knowledge-Based Systems Applications ; Ontologies and the Semantic Web ; Pattern Recognition ; Society, e-Business and e-Government ; Software Engineering ; Symbolic Systems ; Theory and Methods ; Web Information Systems and Technologies

Abstract: Exceptions occurrence in workflow systems is common. Searching in the past exceptions handlers’ records, looking for any similar exception serves as good sources in designing the solution to resolve the exception at hand. In the literature, there are three approaches to retrieve similar workflow exception records from the knowledge base. These approaches are keyword-based approach, concept hierarchies approach and pattern matching retrieval system. However, in a workflow domain, exceptions are often described by workflow participants as a short text using natural language rather than a set of user-defined keywords. Therefore, the above mentioned approaches are not effective in retrieval of relevant information. The proposed approach considers the semantic similarity between the workflow exceptions rather than term-matching schemes, taking account of semantic information and word order information implied in the sentence. Our findings show that sentence similarity measures are capable of supporting the retrieval of relevant information in workflow exception handling knowledge. This paper presents a novel approach to apply sentence similarity measures within the case-based reasoning methodology in workflow exception handling. A data set, comprising of 76 sentence pairs representing instance level workflow exceptions are tested and the results show significant correlation between the automated similarity measures and the human domain expert intuition. (More)

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Paper citation in several formats:
Aldeeb A.; Pearce D.; Crockett K.; Stanton M. and (2010). SENTENCE SIMILARITY MEASURES TO SUPPORT WORKFLOW EXCEPTION HANDLING.In Proceedings of the 12th International Conference on Enterprise Information Systems - Volume 2: ICEIS, ISBN 978-989-8425-05-8, pages 256-263. DOI: 10.5220/0002902502560263

@conference{iceis10,
author={A. Aldeeb and D. M. Pearce and K. Crockett and M. J. Stanton},
title={SENTENCE SIMILARITY MEASURES TO SUPPORT WORKFLOW EXCEPTION HANDLING},
booktitle={Proceedings of the 12th International Conference on Enterprise Information Systems - Volume 2: ICEIS,},
year={2010},
pages={256-263},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002902502560263},
isbn={978-989-8425-05-8},
}

TY - CONF

JO - Proceedings of the 12th International Conference on Enterprise Information Systems - Volume 2: ICEIS,
TI - SENTENCE SIMILARITY MEASURES TO SUPPORT WORKFLOW EXCEPTION HANDLING
SN - 978-989-8425-05-8
AU - Aldeeb, A.
AU - Pearce, D.
AU - Crockett, K.
AU - Stanton, M.
PY - 2010
SP - 256
EP - 263
DO - 10.5220/0002902502560263

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