Title :
Enhancing Domain Knowledge for Requirements Elicitation with Web Mining
Author :
Kaiya, Haruhiko ; Shimizu, Yuutarou ; Yasui, Hirotaka ; Kaijiri, Kenji ; Saeki, Motoshi
Author_Institution :
Dept. of Comput. Sci., Shinshu Univ., Nagano, Japan
fDate :
Nov. 30 2010-Dec. 3 2010
Abstract :
To elicit software requirements, we have to have knowledge about a problem domain, e.g., healthcare, shopping or banking where the software is applied. A description of domain knowledge such as a domain ontology helps requirements analysts to elicit requirements completely and correctly to some extent even if they do not have such knowledge sufficiently. Several requirements elicitation methods and tools using domain knowledge description have been thus proposed, but how to develop and to enhance such description is rarely discussed. Summarizing existing documents related to the domain is one of the typical ways to develop such description, and an interview to domain experts is another typical way. However, requirements cannot be elicited completely only with such domain-specific knowledge because a user of such knowledge, i.e., a requirements analyst is not a domain expert in general. Requirements could be also elicited more correctly with both specific and general knowledge because general knowledge sometimes improves understandings of analysts about domain-specific knowledge. In this paper, we propose a method and a tool to enhance an ontology of domain knowledge for requirements elicitation by using Web mining. In our method and our tool, a domain ontology consists of concepts and their relationships. Our method and tool helps an analyst with a domain ontology to mine general concepts necessary for his requirements elicitation from documents on Web and to add such concepts to the ontology. We confirmed enhanced ontologies contribute to improving the completeness and correctness of elicited requirements through a comparative experiment.
Keywords :
Internet; data mining; formal specification; formal verification; ontologies (artificial intelligence); systems analysis; Web mining; domain knowledge enhancement; domain ontology; domain specific knowledge; requirement analysis; software requirement elicitation; Books; Conference management; Measurement; Ontologies; Software; Web mining; Web pages; Domain Knowledge; Ontology; Requirements Elicitation; Web Mining;
Conference_Titel :
Software Engineering Conference (APSEC), 2010 17th Asia Pacific
Conference_Location :
Sydney, NSW
Print_ISBN :
978-1-4244-8831-5
Electronic_ISBN :
1530-1362
DOI :
10.1109/APSEC.2010.11