3,805 research outputs found

    Integrative Use of Information Extraction, Semantic Matchmaking and Adaptive Coupling Techniques in Support of Distributed Information Processing and Decision-Making

    No full text
    In order to press maximal cognitive benefit from their social, technological and informational environments, military coalitions need to understand how best to exploit available information assets as well as how best to organize their socially-distributed information processing activities. The International Technology Alliance (ITA) program is beginning to address the challenges associated with enhanced cognition in military coalition environments by integrating a variety of research and development efforts. In particular, research in one component of the ITA ('Project 4: Shared Understanding and Information Exploitation') is seeking to develop capabilities that enable military coalitions to better exploit and distribute networked information assets in the service of collective cognitive outcomes (e.g. improved decision-making). In this paper, we provide an overview of the various research activities in Project 4. We also show how these research activities complement one another in terms of supporting coalition-based collective cognition

    Semantic Matchmaking as Non-Monotonic Reasoning: A Description Logic Approach

    Full text link
    Matchmaking arises when supply and demand meet in an electronic marketplace, or when agents search for a web service to perform some task, or even when recruiting agencies match curricula and job profiles. In such open environments, the objective of a matchmaking process is to discover best available offers to a given request. We address the problem of matchmaking from a knowledge representation perspective, with a formalization based on Description Logics. We devise Concept Abduction and Concept Contraction as non-monotonic inferences in Description Logics suitable for modeling matchmaking in a logical framework, and prove some related complexity results. We also present reasonable algorithms for semantic matchmaking based on the devised inferences, and prove that they obey to some commonsense properties. Finally, we report on the implementation of the proposed matchmaking framework, which has been used both as a mediator in e-marketplaces and for semantic web services discovery

    A Configurable Matchmaking Framework for Electronic Marketplaces

    Get PDF
    E-marketplaces constitute a major enabler of B2B and B2C e-commerce activities. This paper proposes a framework for one of the central activities of e-marketplaces: matchmaking of trading intentions lodged by market participants. The framework identifies a core set of concepts and functions that are common to all types of marketplaces and can serve as the basis for describing the distinct styles of matchmaking employed within various market mechanisms. A prototype implementation of the framework based on Web services technology is presented, illustrating its ability to be dynamically configured to meet specific market needs and its potential to serve as a foundation for more fully fledged e-marketplace frameworks

    Matchmaking Framework for B2B E-Marketplaces

    Get PDF
    In the recent years trading on the Internet become more popular. Online businesses gradually replace more and more from the conventional business. Much commercial information is exchanged on the internet, especially using the e-marketplaces. The demand and supply matching process becomes complex and difficult on last twenty years since the e-marketplaces play an important role in business management. Companies can achieve significant cost reduction by using e-marketplaces in their trade activities and by using matchmaking systems on finding the corresponding supply for their demand and vice versa. In the literature were proposed many approaches for matchmaking. In this paper we present a conceptual framework of matchmaking in B2B e-marketplaces environment.B2B Electronic Marketplaces, Conceptual Framework, Matchmaking, Multi- Objective Genetic Algorithm, Pareto Optimal
    • 

    corecore