To work efficiently with DSS, most users need assistance in representation conversion, i. e., translating the specific outcome from the DSS into the universal language of visual. In generally, it is much easier to und...To work efficiently with DSS, most users need assistance in representation conversion, i. e., translating the specific outcome from the DSS into the universal language of visual. In generally, it is much easier to understand the results from the DSS if they are translated into charts, maps, and other scientific displays, because visualization exploits human natural ability to recognize and understand visual pattern. In this paper we discuss the concept of visualization for DSS. AniGraftool, a software system, is introduced as an example of Visualized User Interface for DSS.展开更多
The user interface is a central component of any mo de rn application program. It determines how well end users accept, learn, and effi ciently work with the application program. The user interface is very difficult t...The user interface is a central component of any mo de rn application program. It determines how well end users accept, learn, and effi ciently work with the application program. The user interface is very difficult to design, to implement, to modify. It takes approximately 70% of the time requ ired for designing an application program. All the existing tools for user interface design can be divided into two basic c ategories-Interface Builders and Model-based Interface development tools, whic h trace their roots from user interface management systems. Interface Builders a re the most widespread and excellent to create layouts and manipulate widgets. H owever, Interface Builders have the follow demerits. An interface designed using Interface Builders can contain hundreds of procedures. Interface Builders give us no possibility to develop different pieces of the same interface separately. They do not help us in managing user tasks and can be used only by programmers. Model-based interface development tools have attracted a high degree of interes t in last few years. The basic premise of model based technology is that the interface development can be fully supported by declarative models of all user interface characteristics such as their presen tation, dialogue, domain of application etc, and then the user interface develop ment can be centered around such models. The high potential of this technology has not been realized yet. This fact has the following reasons. The known interface models are partial representations of interfaces. They cannot be readily modified by developers, and are not publicly available to the HCI community. The central ingredient for success in model-ba sed systems is a declarative, complete, versatile interface model that can expre ss a wide variety of interface designs. Therefore tool developers have to avoid the following disadvantages of current interface models: inflexibility, system- dependence, and incompleteness. The main idea to achieve these model character istics mention above is to use ontologies. This broadened interest in ontologies is based on the fact that they provide ma chine-understandable representation of semantics for information, and a shared and common understanding of a domain that can be communicated between people and across application systems. Support in data, information, and knowledge exchang e becomes the key issue in current computer technology. At the moment we are on the brink of the second Web generation called Semantic Web or Knowledgeable Web. Given the increasing amount of information available on-line, this kind of sup port is becoming more important day by day. The main idea of the proposed approach is to replace interface models by appropr iate ontologies. Some parts of these ontologies will be available from the Inter net; the other parts will be built by developers. As a result of the Semantic We b development we will have increasing the number of ontologies formally describe d in the Internet. The terminology and content of these ontologies will be inter nationally standardized. Reusing these ontologies will bring down the cost of de velopment and improve the quality of user interface. The parts of a user interface model are-a domain ontology model, a dialog ontol ogy model, presentation ontology model, "business- logic" variable ontology mod el and correspondences between these parts. Thus, the user interface development based on ontologies is an evolution of th e model-based approach, where appropriate ontologies are used instead of models .展开更多
There has been an increasing interest in integrating decision support systems (DSS) and expert systems (ES) to provide decision makers a more accessible, productive and domain-independent information and computing env...There has been an increasing interest in integrating decision support systems (DSS) and expert systems (ES) to provide decision makers a more accessible, productive and domain-independent information and computing environment. This paper is aimed at designing a multiple expert systems integrated decision support system (MESIDSS) to enhance decision makers' ability in more complex cases. The basic framework, management system of multiple ESs, and functions of MESIDSS are presented. The applications of MESIDSS in large-scale decision making processes are discussed from the following aspects of problem decomposing, dynamic combination of multiple ESs, link of multiple bases and decision coordinating. Finally, a summary and some ideas for the future are presented.展开更多
文摘To work efficiently with DSS, most users need assistance in representation conversion, i. e., translating the specific outcome from the DSS into the universal language of visual. In generally, it is much easier to understand the results from the DSS if they are translated into charts, maps, and other scientific displays, because visualization exploits human natural ability to recognize and understand visual pattern. In this paper we discuss the concept of visualization for DSS. AniGraftool, a software system, is introduced as an example of Visualized User Interface for DSS.
文摘The user interface is a central component of any mo de rn application program. It determines how well end users accept, learn, and effi ciently work with the application program. The user interface is very difficult to design, to implement, to modify. It takes approximately 70% of the time requ ired for designing an application program. All the existing tools for user interface design can be divided into two basic c ategories-Interface Builders and Model-based Interface development tools, whic h trace their roots from user interface management systems. Interface Builders a re the most widespread and excellent to create layouts and manipulate widgets. H owever, Interface Builders have the follow demerits. An interface designed using Interface Builders can contain hundreds of procedures. Interface Builders give us no possibility to develop different pieces of the same interface separately. They do not help us in managing user tasks and can be used only by programmers. Model-based interface development tools have attracted a high degree of interes t in last few years. The basic premise of model based technology is that the interface development can be fully supported by declarative models of all user interface characteristics such as their presen tation, dialogue, domain of application etc, and then the user interface develop ment can be centered around such models. The high potential of this technology has not been realized yet. This fact has the following reasons. The known interface models are partial representations of interfaces. They cannot be readily modified by developers, and are not publicly available to the HCI community. The central ingredient for success in model-ba sed systems is a declarative, complete, versatile interface model that can expre ss a wide variety of interface designs. Therefore tool developers have to avoid the following disadvantages of current interface models: inflexibility, system- dependence, and incompleteness. The main idea to achieve these model character istics mention above is to use ontologies. This broadened interest in ontologies is based on the fact that they provide ma chine-understandable representation of semantics for information, and a shared and common understanding of a domain that can be communicated between people and across application systems. Support in data, information, and knowledge exchang e becomes the key issue in current computer technology. At the moment we are on the brink of the second Web generation called Semantic Web or Knowledgeable Web. Given the increasing amount of information available on-line, this kind of sup port is becoming more important day by day. The main idea of the proposed approach is to replace interface models by appropr iate ontologies. Some parts of these ontologies will be available from the Inter net; the other parts will be built by developers. As a result of the Semantic We b development we will have increasing the number of ontologies formally describe d in the Internet. The terminology and content of these ontologies will be inter nationally standardized. Reusing these ontologies will bring down the cost of de velopment and improve the quality of user interface. The parts of a user interface model are-a domain ontology model, a dialog ontol ogy model, presentation ontology model, "business- logic" variable ontology mod el and correspondences between these parts. Thus, the user interface development based on ontologies is an evolution of th e model-based approach, where appropriate ontologies are used instead of models .
文摘There has been an increasing interest in integrating decision support systems (DSS) and expert systems (ES) to provide decision makers a more accessible, productive and domain-independent information and computing environment. This paper is aimed at designing a multiple expert systems integrated decision support system (MESIDSS) to enhance decision makers' ability in more complex cases. The basic framework, management system of multiple ESs, and functions of MESIDSS are presented. The applications of MESIDSS in large-scale decision making processes are discussed from the following aspects of problem decomposing, dynamic combination of multiple ESs, link of multiple bases and decision coordinating. Finally, a summary and some ideas for the future are presented.
