Publications

A belief-theoretic framework for the collaborative development and integration of para-consistent conceptual models

Ebrahim Bagheri and Ali A. Ghorbani
Reference:
Ebrahim Bagheri and Ali A. Ghorbani A belief-theoretic framework for the collaborative development and integration of para-consistent conceptual models. In Journal of Systems and Software, 82 (4): 707-729, 2009.
Links to Publication: [doi]
Abstract:
Merging and integrating different conceptual models which have been collaboratively developed by domain experts and analysts with dissimilar perspectives on the same issue has been the subject of tremendous amount of research. In this paper, we focus on the fact that human analysts' opinions possess a degree of uncertainty which can be exploited while integrating such information. We propose an underlying modeling construct which is the basis for transforming conceptual models into a manipulatable format. Based on this construct, methods for formally negotiating over and merging of conceptual models are proposed. The approach presented in this paper focuses on the formalization of uncertainty and expert reliability through the employment of belief theory. The proposed work has been evaluated for its effectiveness and usability. The evaluators (a group of Computer Science graduate students) believed that the proposed framework has the capability to fulfil its intended tasks. The obtained results from the performance perspective are also promising.
Bibtex Entry:
@article{DBLP:journals/jss/BagheriG09, author = {Ebrahim Bagheri and Ali A. Ghorbani}, title = {A belief-theoretic framework for the collaborative development and integration of para-consistent conceptual models}, journal = {Journal of Systems and Software}, volume = {82}, number = {4}, year = {2009}, pages = {707-729}, ee = {http://dx.doi.org/10.1016/j.jss.2008.10.012}, bibsource = {DBLP, http://dblp.uni-trier.de}, abstract = {Merging and integrating different conceptual models which have been collaboratively developed by domain experts and analysts with dissimilar perspectives on the same issue has been the subject of tremendous amount of research. In this paper, we focus on the fact that human analysts' opinions possess a degree of uncertainty which can be exploited while integrating such information. We propose an underlying modeling construct which is the basis for transforming conceptual models into a manipulatable format. Based on this construct, methods for formally negotiating over and merging of conceptual models are proposed. The approach presented in this paper focuses on the formalization of uncertainty and expert reliability through the employment of belief theory. The proposed work has been evaluated for its effectiveness and usability. The evaluators (a group of Computer Science graduate students) believed that the proposed framework has the capability to fulfil its intended tasks. The obtained results from the performance perspective are also promising.} }




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