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

How Ontologies Can Help in an eMarketplace

Recently, ontologies have been developed in various business domains with the recent maturing of the Semantic Web technologies. However, ontology-related researches have largely focused on the facilitation of successful matchmaking but not much on traders’ requirement elicitation and potential negotiations in e-marketplaces. Because ontology provides the key knowledge about the inter-relationships among the issues and alternatives of the traders’ requirements, we show how to elicit trade requirements, alternatives, and tradeoff from an agreed ontology. This facilitates the whole business process of the e-marketplace, from matchmaking, recommendation, to negotiation. We further propose a novel methodology for the elicitation of dependencies among traders’ requirements for the formulation of an effective decision plan. As a result, traders can have a better cognition of their requirements and the overall operations of the e-marketplace can be streamlined

Performance analysis of static agent architecture with centralized matchmaking

Text in English; Abstract: English and TurkishIncludes bibliographical references (leaves 46-50)ix, 50 leavesLarge- scale network environments such as the internet possess the characteristics of distributed data, distributed access and distributed control. This gives users a powerful mechanism for building and integrating large amounts of distributed information from diverse resources. However few support tools have been developed for users to sift through this vast amount of information. In this thesis, we advocate the integration of two entities; Static agents to create a user profile, and information integration architecture to provide the desired information. Text-Based information is the main concern due to its high significance in our daily lives. Thus, information integration architecture will gather and intelligently combine information from multiple agents and present the user with combined information using a task agent.İnternet ve ona benzer büyük boyuttaki ağ yapıları dağıtık veri, dağıtık erişim ve dağıtık kontrol imkanları sağlar. Bu sayede kullanıcılar, büyük miktarlardaki veriyi farklı kaynaklardan alıp birleştirme ve yapılandırma şansına sahip olurlar. Ancak bu büyük boyutlardaki veriyi belli bir amaca göre eleyebilecek destek araçları sınırlı sayıdadır. Bu tezde iki varlığın bir araya getirilmesi savunulmaktadır. Durağan ajanlar ile kullanıcı profili yaratmak ve bilgi entegrasyon mimarisi ile gerekli bilgiyi kullanıcılara sağlamak hedeflenmiştir. Karakter tabanlı bilgi günlük hayatımızdaki öneminden dolayı tezin ürettiği çözüm içinde yer almaktadır. Böylece bilgi entegrasyon mimarisi farklı durağan ajanlardan bilgi toplayıp, derleyip talep eden diğer ajanlara sunacaktır. Bunu yaparken görev ajanı kullanılacaktır

An intelligent framework for dynamic web services composition in the semantic web

As Web services are being increasingly adopted as the distributed computing technology of choice to securely publish application services beyond the firewall, the importance of composing them to create new, value-added service, is increasing. Thus far, the most successful practical approach to Web services composition, largely endorsed by the industry falls under the static composition category where the service selection and flow management are done a priori and manually. The second approach to web-services composition aspires to achieve more dynamic composition by semantically describing the process model of Web services and thus making it comprehensible to reasoning engines or software agents. The practical implementation of the dynamic composition approach is still in its infancy and many complex problems need to be resolved before it can be adopted outside the research communities. The investigation of automatic discovery and composition of Web services in this thesis resulted in the development of the eXtended Semantic Case Based Reasoner (XSCBR), which utilizes semantic web and AI methodology of Case Based Reasoning (CBR). Our framework uses OWL semantic descriptions extensively for implementing both the matchmaking profiles of the Web services and the components of the CBR engine. In this research, we have introduced the concept of runtime behaviour of services and consideration of that in Web services selection. The runtime behaviour of a service is a result of service execution and how the service will behave under different circumstances, which is difficult to presume prior to service execution. Moreover, we demonstrate that the accuracy of automatic matchmaking of Web services can be further improved by taking into account the adequacy of past matchmaking experiences for the requested task. Our XSCBR framework allows annotating such runtime experiences in terms of storing execution values of non-functional Web services parameters such as availability and response time into a case library. The XSCBR algorithm for matchmaking and discovery considers such stored Web services execution experiences to determine the adequacy of services for a particular task. We further extended our fundamental discovery and matchmaking algorithm to cater for web services composition. An intensive knowledge-based substitution approach was proposed to adapt the candidate service experiences to the requested solution before suggesting more complex and computationally taxing AI-based planning-based transformations. The inconsistency problem that occurs while adapting existing service composition solutions is addressed with a novel methodology based on Constraint Satisfaction Problem (CSP). From the outset, we adopted a pragmatic approach that focused on delivering an automated Web services discovery and composition solution with the minimum possible involvement of all composition participants: the service provider, the requestor and the service composer. The qualitative evaluation of the framework and the composition tools, together with the performance study of the XSCBR framework has verified that we were successful in achieving our goal

A Semantic Grid Oriented to E-Tourism

With increasing complexity of tourism business models and tasks, there is a clear need of the next generation e-Tourism infrastructure to support flexible automation, integration, computation, storage, and collaboration. Currently several enabling technologies such as semantic Web, Web service, agent and grid computing have been applied in the different e-Tourism applications, however there is no a unified framework to be able to integrate all of them. So this paper presents a promising e-Tourism framework based on emerging semantic grid, in which a number of key design issues are discussed including architecture, ontologies structure, semantic reconciliation, service and resource discovery, role based authorization and intelligent agent. The paper finally provides the implementation of the framework.Comment: 12 PAGES, 7 Figure

An architecture for user preference-based IoT service selection in cloud computing using mobile devices for smart campus

The Internet of things refers to the set of objects that have identities and virtual personalities operating in smart spaces using intelligent interfaces to connect and communicate within social environments and user context. Interconnected devices communicating to each other or to other machines on the network have increased the number of services. The concepts of discovery, brokerage, selection and reliability are important in dynamic environments. These concepts have emerged as an important field distinguished from conventional distributed computing by its focus on large-scale resource sharing, delivery and innovative applications. The usage of Internet of Things technology across different service provisioning environments has increased the challenges associated with service selection and discovery. Although a set of terms can be used to express requirements for the desired service, a more detailed and specific user interface would make it easy for the users to express their requirements using high-level constructs. In order to address the challenge of service selection and discovery, we developed an architecture that enables a representation of user preferences and manipulates relevant descriptions of available services. To ensure that the key components of the architecture work, algorithms (content-based and collaborative filtering) derived from the architecture were proposed. The architecture was tested by selecting services using content-based as well as collaborative algorithms. The performances of the algorithms were evaluated using response time. Their effectiveness was evaluated using recall and precision. The results showed that the content-based recommender system is more effective than the collaborative filtering recommender system. Furthermore, the results showed that the content-based technique is more time-efficient than the collaborative filtering technique