The study proposes a framework of ONTOlogy-based Group Decision Support System (ONTOGDSS) for decision process which exhibits the complex structure of decision-problem and decision-group. It is capable of reducing the complexity of problem structure and group relations. The system allows decision makers to participate in group decision-making through the web environment, via the ontology relation. It facilitates the management of decision process as a whole, from criteria generation, alternative evaluation, and opinion interaction to decision aggregation. The embedded ontology structure in ONTOGDSS provides the important formal description features to facilitate decision analysis and verification. It examines the software architecture, the selection methods, the decision path, etc. Finally, the ontology application of this system is illustrated with specific real case to demonstrate its potentials towards decision-making development.
Decision Support Systems (DSS) have been proposed since the late 1960s to help decision maker improve the efficiency and correctness in decision making. Along the development of DSS, researchers notice that the decision making in reality is not just individual decision but often involving multiple peoples. As a matter of fact, many decision problems (such as great strategic decision of government or industry, the managing decision of large company), have the complex internal structure and in need of making decision by a large decision group with complex relationship among people. To address these problems, we provide a group decision process structure and system framework coupled with relatively complex decision groups and tasks.
In section 2, we investigate the task decomposition and group selection process based on the analysis of the ontology structure in the application domain, in order to reduce the complexity of them. Section 3 provides the design of a sub-system named Workshop System, in order to resolve the conflict in group decision process. It describes the use of ontology approach and metasynthesis methodology [10] for designing the group argumentation models. Section 4 leads to the ontology-driven system framework including the overall group decision process, system architecture, and ONTOGDSS hierarchical structure with ontology-based decision resource layer. Finally, section 5 presents an ontology application in decision-problem domain with illustrative examples.
Ontology is defined as “a set of knowledge terms, including the vocabulary, the semantic interconnections and some simple rules of inference and logic, for some particular topic” [1]. That is to say, ontology captures the model of knowledge for a particular domain. They allow us to describe resources on the web and the relationships between those resources. Accordingly, ontology can be regarded as metadata which play an important role in decision process. System provides the methods for generating a series of alternatives for comparison and evaluation of different decision-makers. Thus, ONTOGDSS relies on metadata to describe the attributes, objectives, context, constraints, types, criteria of the complex decision problem in real world, and therefore will be ontology-driven. So, it is necessary to develop ontologies which can encode the semantic representation of the structural complex decision problem, in order to form a specific, clear decision path.
Based on Herhert A Simon’s [2] dichotomy of decision problem, we develop the idea of dividing decision problems into three categories: structural problem, semi-structural problem and non-structural problem. For structural problems, we can load decision models, methods, data and other information as reference. For other two problems, since semi-structural and non-structural problems mean that they have never been shown up before and usually presented as qualitative textual form/document with complex semantic structure, therefore, besides loading necessary data in database, it is important to make the reference via ontology-approached knowledge management system in various decision domains.
The ONTOGDSS is designed as an ontology-based intelligent information system platform. It highlights the needs for considering contextual aspects in system perspective. Besides, ontology in specific decisionproblem domains would include basic concepts such as decision targets, principles, limitations, and additional concepts of problem style, characteristics, evaluation criteria and etc. Therefore, problem representative and description in ontology approach are not only important to those structure-problems for better searching and matching in previous models or methods, but also used especially for those semi-structure/non-structure problems for group decision process.
DSS ontology can be defined as formal descriptions of decision concepts by basic terms and relationships as well as the rules for combining these terms in a certain problem domain. While abstraction of an ontology development is similar to definition of a conceptual model, the focus is on extended definitions of relationships and concepts, and having the explicit goal of reuse and sharing knowledge by using a common framework. In GDSSs, the concept of decision-group usually is presented in contextual form with complicated relationship and structure. However, the concept of group is usually defined in literature as a kind of individual-aggregated entity which does not depend on individual properties with conceptualization. This paper analyzes and establishes the decision-group through ontology-based conceptual extraction in contextual decision-group domain. This approach can eliminate the confusions associated with the term “Group”. Once various structures are established, the unique characteristics of each would be emerged. Thus, researches can be focused on the various interactions among participants as well.
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