Matchmaking Semantic based for Information System Interoperability

Unlike the traditional model of information pull, matchmaking is base on a cooperative partnership between information providers and consumers, assisted by an intelligent facilitator (the matchmaker). Refer to some experiments, the matchmaking to be most useful in two different ways: locating information sources or services that appear dynamically and notification of information changes. Effective information and services sharing in distributed such as P2P based environments raises many challenges, including discovery and localization of resources, exchange over heterogeneous sources, and query processing. One traditional approach for dealing with some of the above challenges is to create unified integrated schemas or services to combine the heterogeneous sources. This approach does not scale well when applied in dynamic distributed environments and has many drawbacks related to the large numbers of sources. The main issues in matchmaking are how to represent advertising and request, and how to calculate possibility matching between advertising and request. The advertising and request can represent data or services by using many model of representation. In this paper, we address an approach of matchmaking by considering semantic agreement between sources

Matchmaking Semantic Based for Information System Interoperability

Unlike the traditional model of information pull, matchmaking is base on a cooperative partnership between information providers and consumers, assisted by an intelligent facilitator (the matchmaker). Refer to some experiments, the matchmaking o be most useful in two different ways: locating information sources or services that appear dynamically and notification of nformation changes. Effective information and services sharing in distributed such as P2P based environments raises many challenges, including discovery and localization of resources, exchange over heterogeneous sources, and query processing. One raditional approach for dealing with some of the above challenges is to create unified integrated schemas or services to combine the heterogeneous sources. This approach does not scale well when applied in dynamic distributed environments and has many drawbacks related to the large numbers of sources. The main issues in matchmaking are how to represent advertising and request, and how to calculate possibility matching between advertising and request. The advertising and request can epresent data or services by using many model of representation. In this paper, we address an approach of matchmaking by considering semantic agreement between sources

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

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 description logic based approach for matching user profiles

Several applications require the matching of user profiles, e.g., job recruitment or dating systems. In this paper we present a logical framework for specifying user profiles that allows profile description to be incomplete in the parts that are unavailable or are considered irrelevant by the user. We present an algorithm for matching demands and supplies of profiles, taking into account incompleteness of profiles and incompatibility between demand and supply. We specialize our framework to dating services; however, the same techniques can be directly applied to several other contexts