The Experts below are selected from a list of 288660 Experts worldwide ranked by ideXlab platform
Guisseppi A Forgionne - One of the best experts on this subject based on the ideXlab platform.
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A Conceptual Model for Knowledge Marts for Decision Making Support Systems
International Journal of Decision Support System Technology, 2012Co-Authors: Hayden Wimmer, Guisseppi A Forgionne, Roy Rada, Victoria Y. YoonAbstract:This paper provides an integrated and comprehensive conceptual framework for knowledge based Decision Making Support systems. Previous research has focused primarily on general Decision Support systems. The paper extends the previous work by presenting a framework to Support specific Decisions using knowledge marts that contain Decision pertinent knowledge. A proposed methodology to test the effectiveness of this new model is proposed. The model presented provides much more specific knowledge Support than previous systems.
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An experiment on the effectiveness of creativity enhancing Decision-Making Support systems
Decision Support Systems, 2007Co-Authors: Guisseppi A Forgionne, John NewmanAbstract:Recent research suggests that creativity can enhance the performance of people for a variety of tasks, including Decision-Making. Creativity enhancements can be delivered through a Decision-Making Support system. In theory, such delivery should improve the Decision performance of the system's user. This paper tests the theory empirically and discusses the implications for Decision-Making.
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intelligent Decision Making Support systems foundations applications and challenges
2006Co-Authors: Jatinder N D Gupta, Guisseppi A Forgionne, Manuel MoraAbstract:Part I Foundations of i-DMSS A Multi-criteria Model for the Evaluation of Intelligent Decision-Making Support Systems (i-DMSS) On the Legacy of Herbert Simon and his contribution to Decision Making Support Systems and Artificial Intelligence Synergizing the Artificial Intelligence and Decision Support Research Streams: Over a Decade of Progress with New Challenges on the Horizon From Knowledge Discovery to Computational Intelligence: A Framework for Intelligent Decision Support Systems Taking Decisions into the Wild: An AI Perspective in the Design of i-DMSS Development Processes of Intelligent Decision Making Support Systems: Review and Perspective Explanatory Power of Intelligent Systems: Review and Perspective Part II Applications of i-DMSS A New Paradigm for Developing intelligent Decision-Making Support Systems (i-DMSS): A Case Study on the Development of Comparison-Shopping Agents A Causal Knowledge-Driven Negotiation Mechanism for B2B Electronic Commerce A Simulation Study of Just-In-Time Knowledge Management (JITKM) An IDSS for Regional Aquaculture Planning An i-DMSS Based on Bipartite Matching and Heuristics for Rental Bus Allocation MicroDEMON: A Decision-Making Intelligent Assistant for Mobile Business Using System Dynamics and Case Based Reasoning (CBR) to build an Intelligent Decision-Making Support System (i-DMSS) that improves Strategic Public Decisions e-Negotiation Systems and Software Agents: Methods, Models, and Applications Knowledge-Intensive Collaborative Decision Support for Design Process The Application of Semantic Web Technologies for Railway Decision Support Part III Trends of i-DMSS The Challenge of Supporting Emerging Inference-Based Decision Making A Role for Information Portals as Intelligent Decision Support Systems: Breast Cancer Knowledge On-Line Experience An Overview of Future Challenges of Decision Support Technologies A challenging future for i-DMSS A Software Laboratory for Advancing Decision Support Simulation A Strategic Descriptive Review of Intelligent Decision-Making Support Systems Research: the 1980-2004 Period The Optimization of What?
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Encyclopedia of Information Science and Technology (II) - Decision-Making Support Systems
Encyclopedia of Information Science and Technology First Edition, 2005Co-Authors: Guisseppi A Forgionne, Manuel Mora, Jatinder N D Gupta, Ovsei GelmanAbstract:Decision-Making Support systems (DMSS) are computer-based information systems designed to Support some or all phases of the Decision-Making process (Forgionne, Mora, Cervantes, & Kohli, 2000). There are Decision Support systems (DSS), executive information systems (EIS), and expert systems/knowledge-based systems (ES/KBS). Indi-vidual EIS, DSS, and ES/KBS, or pair-integrated combina-tions of these systems, have yielded substantial benefits in practice. DMSS evolution has presented unique challenges and opportunities for information system professionals. To gain further insights about the DMSS field, the original version of this article presented expert views regarding achievements, challenges, and opportunities, and examined the implica-tions for research and practice (Forgionne, Mora, Gupta, & Gelman, 2005). This article updates the original version by offering recent research findings on the emerging area of intelligent Decision-Making Support systems (IDMSS). The title has been changed to reflect the new content.
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KES - Intelligent Decision Making Support through Just-in-Time Knowledge Management
Lecture Notes in Computer Science, 2003Co-Authors: Nabie Y. Conteh, Guisseppi A ForgionneAbstract:This paper will offer an intelligent Decision Making Support system that integrates knowledge management and Decision Support technologies. First, the paper overviews the link between knowledge management and Decision Making Support. Next, the paper presents a research plan for empirically measuring the outcome and process improvements that can be achieved through the knowledge-based Decision Making Support system in the software engineering field. Then, there is a discussion of the implications for information systems research and practice.
Xu Ying-zhuo - One of the best experts on this subject based on the ideXlab platform.
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Visualization Decision-Making Support System for Oilfield Accident Emergency Rescue
Computer Engineering, 2010Co-Authors: Xu Ying-zhuoAbstract:Aiming at the lack of current emergency rescue mechanisms for oilfield accidents,this paper proposes a visualization Decision-Making Support system for oilfield accident emergency rescue based on WebGIS.It combines all levels of emergency rescue command organizations in different locations by network,thereby cooperating to emergency rescue.And it provides all-side,visualization and high-efficiency information services,along with Decision-Making Support so as to improve emergency rescue in terms of scientific and real-time characters.Its architecture and key techniques of the system are presented,including asynchronous communication between the client and the server,load and display of map,and model of optimal rescue path algorithm.
Claudio Sapateiro - One of the best experts on this subject based on the ideXlab platform.
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Integrating Decision-Making Support in Geocollaboration Tools
Group Decision and Negotiation, 2014Co-Authors: Pedro Antunes, Gustavo Zurita, Nelson Baloian, Claudio SapateiroAbstract:Collaborative spatial Decision Making (CSDM) involves multiple stakeholders Making strategic Decisions based on spatial data. Current CSDM tools have been exploring different ways to integrate spatial data with collaboration, distribution and mobility. Notably, Decision-Making Support has not seen the same level of attention. This paper discusses the challenges raised by the integration of Decision-Making models in CSDM tools. We review a large collection of Decision-Making models using three different views: sequential, dynamic and continuous. From this review we derive a conceptual model and a set of functional requirements necessary to integrate Decision-Making Support in CSDM tools. The conceptual model highlights the importance of several functions in Decision-Making processes: representing problems, finding alternatives and Making choices (sequential view); classification and communication (dynamic view); and perception, comprehension and projection (continuous view). The paper also describes a prototype developed to validate the model. The paper provides two main research contributions: a unified view of Decision-Making Support and an innovative CSDM tool blending spatial data with Decision-Making Support.
Francisco Cervantes - One of the best experts on this subject based on the ideXlab platform.
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KES - A Framework to Assess Intelligent Decision-Making Support Systems
Lecture Notes in Computer Science, 2003Co-Authors: Manuel Mora, Guisseppi A Forgionne, Jatinder N D Gupta, Francisco Cervantes, Ovsei GelmanAbstract:A new framework to identify and classify the Support capabilities provided by the full range of Decision-Making Support Systems is posed. This framework extends a previously reported framework by the same authors. The new framework adds a dimension of user interface Support capabilities to the data, information and knowledge representation and processing capabilities dimensions of the previous framework. With this conceptual tool, an analysis of the achievements realized and a research agenda for the next generation of Intelligent DMSS is developed.
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The Implementation of Large-Scale Decision-Making Support Systems
Encyclopedia of Decision Making and Decision Support Technologies, 1Co-Authors: Manual Mora, Ovsei Gelman, Guisseppi Forgionne, Francisco CervantesAbstract:This article reviews the literature-based issues involved in implementing large-scale Decision-Making Support systems (DMSSs). Unlike previous studies, this review studies holistically three types of DMSSs (model-based Decision Support systems, executive-oriented Decision Support systems, and knowledge-based Decision Support systems) and incorporates recent studies on the simulation of the implementations process. Such an article contributes to the literature by organizing the fragmented knowledge on the DMSS implementation phenomenon and by communicating the factors and stages involved in successful or failed large-scale DMSS implementations to practitioners.
Pedro Antunes - One of the best experts on this subject based on the ideXlab platform.
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Integrating Decision-Making Support in Geocollaboration Tools
Group Decision and Negotiation, 2014Co-Authors: Pedro Antunes, Gustavo Zurita, Nelson Baloian, Claudio SapateiroAbstract:Collaborative spatial Decision Making (CSDM) involves multiple stakeholders Making strategic Decisions based on spatial data. Current CSDM tools have been exploring different ways to integrate spatial data with collaboration, distribution and mobility. Notably, Decision-Making Support has not seen the same level of attention. This paper discusses the challenges raised by the integration of Decision-Making models in CSDM tools. We review a large collection of Decision-Making models using three different views: sequential, dynamic and continuous. From this review we derive a conceptual model and a set of functional requirements necessary to integrate Decision-Making Support in CSDM tools. The conceptual model highlights the importance of several functions in Decision-Making processes: representing problems, finding alternatives and Making choices (sequential view); classification and communication (dynamic view); and perception, comprehension and projection (continuous view). The paper also describes a prototype developed to validate the model. The paper provides two main research contributions: a unified view of Decision-Making Support and an innovative CSDM tool blending spatial data with Decision-Making Support.
