Computationally efficient ontology selection in software requirement planning

Computationally efficient ontology selection in software requirement planning

Understanding the needs of stakeholders and prioritizing requirements are the vital steps in the development of any software application. Enabling tools to support these steps have a critical role in the success of the corresponding software application. Based on such a critical role, this paper pre...

Full description

Saved in:
Bibliographic Details
Published in:Information systems frontiers Vol. 18; no. 2; pp. 349 - 358
Main Authors: Brown, R. B. K., Beydoun, G., Low, G., Tibben, W., Zamani, R., García-Sánchez, F., Martinez-Bejar, R.
Format: Journal Article
Language:English
Published: New York Springer US 01-04-2016
Springer Nature B.V
Subjects:
Analysis
Applications programs
Business and Management
Computational efficiency
Computer programs
Control
Design
Design engineering
Information science
Information systems
IT in Business
Knowledge representation
Language
Management of Computing and Information Systems
Natural language
Ontology
Operations Research/Decision Theory
Requirements
Semantic web
Semantics
Software
Stakeholders
Studies
Systems design
Systems Theory
Taxonomy
Ontologies
Retrieval tool
Process models
Requirements
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Understanding the needs of stakeholders and prioritizing requirements are the vital steps in the development of any software application. Enabling tools to support these steps have a critical role in the success of the corresponding software application. Based on such a critical role, this paper presents a computationally efficient ontology selection in software requirement planning. The key point guiding the underlying design is that, once gathered, requirements need to be processed by decomposition towards the generation of a specified systems design. A representational framework allows for the expression of high level abstract conceptions under a single schema, which may then be made explicit in terms of axiomatic relations and expressed in a suitable ontology. The initial experimental results indicate that our framework for filtered selection of a suitable ontology operates in a computationally efficient manner.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
ISSN:1387-3326
1572-9419
DOI:10.1007/s10796-014-9540-3