Semantic requirements sharing approach to develop software systems using concept maps and information entropy: A Personal Health Information System example

Authors:
Varadraj P. Gurupur;Unal Sakoglu;G. Pankaj Jain;U. John Tanik
Affiliations:
Health Informatics and Information Management, Louisiana Tech University, United States;Department of Computer Science and Information Systems, Texas A&M University - Commerce, United States;Department of Computer Science and Information Systems, Texas A&M University - Commerce, United States;Department of Computer Science, Indiana University - Purdue University Fort Wayne, United States
Venue:
Advances in Engineering Software
Year:
2014

Citing 20
Cited 0

Fundamentals of computing for software engineers

Fundamentals of computing for software engineers
Knowledge engineering and management: the CommonKADS methodology

Knowledge engineering and management: the CommonKADS methodology
JAX: Java APIs for XML Kick Start

JAX: Java APIs for XML Kick Start
Variability as a measure of semantic structure for document storage and retrieval

Variability as a measure of semantic structure for document storage and retrieval
Digital Concept Mapping in Learning Contexts: Integrating Knowledge, Arguments and Information Resources

IV '05 Proceedings of the Ninth International Conference on Information Visualisation
Understanding .NET (2nd Edition)

Understanding .NET (2nd Edition)
Supervised Learning of Semantic Classes for Image Annotation and Retrieval

IEEE Transactions on Pattern Analysis and Machine Intelligence
Bridging the Semantic Gap: Visualizing Transition Graphs with User-Defined Diagrams

IEEE Computer Graphics and Applications
Linking Semantic and Knowledge Representations in a Multi-Domain Dialogue System

Journal of Logic and Computation
Semantic Web for the Working Ontologist: Effective Modeling in RDFS and OWL

Semantic Web for the Working Ontologist: Effective Modeling in RDFS and OWL
Systematic Component-Oriented development with Axiomatic Design

Journal of Systems and Software
An architecture framework for composite services with process-personalization

An architecture framework for composite services with process-personalization
Defining an OWL Ontology That Could Be Used to Integrate Mental-Health Risk Information within a Decision Support System

ETELEMED '09 Proceedings of the 2009 International Conference on eHealth, Telemedicine, and Social Medicine
Predicting problem-solving performance with concept maps: An information-theoretic approach

Decision Support Systems
Programming-by-Example Meets the Semantic Web: Using Ontologies and Web Services to Close the Semantic Gap

VLHCC '10 Proceedings of the 2010 IEEE Symposium on Visual Languages and Human-Centric Computing
A System for Building Clinical Research Applications using Semantic Web-Based Approach

Journal of Medical Systems
Bridging the semantic gap between abstract models of embedded systems

CBSE'10 Proceedings of the 13th international conference on Component-Based Software Engineering
A Kind of Map Coloring Algorithm Considering of Depth First Search

ICICEE '12 Proceedings of the 2012 International Conference on Industrial Control and Electronics Engineering
An Approach for Building a Personal Health Information System Using Conceptual Domain Knowledge

Journal of Medical Systems
C-PHIS: A Concept Map-Based Knowledge Base Framework to Develop Personal Health Information Systems

Journal of Medical Systems

Quantified Score

Hi-index	0.00

Visualization

Abstract

In this paper we describe a process of developing software systems by capturing the conceptual domain knowledge of the problem domain using concept maps. To illustrate the implementation of this process we have used the example of developing Personal Health Information Systems. In addition to the aforementioned development process, the paper also describes an evaluation metric developed using Design Structure Matrix and information entropy to measure the structural properties of the concept map. The determination of entropy is based on the information derived from the hierarchical structure of a concept map. The probability distributions and the information entropy were calculated defining a new metric: node source connectivity strength based on the number of unique paths from a node to another. The results were compared by using a more standard metric, the graph node connectivity.