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Dhavalkumar Thakker Home | PhD | Projects | Publications | Contact |
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Bridging the Gap between Semantic and Non-Semantic standards for Web services Composition Semantic Case Based Reasoner (S-CBR) for Web services Discovery and Matchmaking Semantic Spatial Web Services with Case-Based Reasoning Integrative Semantic Framework for Image Annotation and Retrieval
Bridging the Gap between Semantic and Non-Semantic standards for Web services Composition The most practically deployed Web services composition techniques use the theory of business workflow-management as composition process model to achieve formalization for control and data flow. Mainly based on the Business Process Execution Language (BPEL) standard, these techniques also have practical capabilities that fulfil the needs of the business environment, such as fault handling and state management. However, the main shortcoming of these techniques is the static composition approach, where the service selection and flow management are done a priori and manually. In contrast, composition techniques based on the semantic web, such as Ontology Web Language for Web services (OWL-S), use ontologies to provide a mechanism to describe the Web services functionality in machine-understandable form, making it possible to discover, and integrate Web services automatically. The focus of this project was on bridging the gap between the two approaches by introducing semantics to workflow-based composition. Developed framework exploits the BPEL process creation mechanism combined with semantic domain concept (OWL) to implement an automatic composition-programming framework providing a hybrid solution that merges the benefit of practicality of use and adoption popularity of workflow-based composition. Framework has advantage of using semantic description to aid both service developers and composers in the composition process and facilitating the dynamic integration of Web services into it. The paper [Bridging the Gap between Workflow and Semantic-based Web services Composition] provides more detail on implementation. Publications related to this project are as follows: Publications
Semantic Case Based Reasoner (S-CBR) for Web services Discovery and Matchmaking Web services are being increasingly adopted as the computing engine of choice for today's Internet-driven applications. The composition of Web services further advances their advantages by allowing different services to integrate for providing new, value-added services. The automated discovery of adequate Web services is the pre-requisite and core feature for achieving dynamic Web services composition. In this project, we experiment a new approach that utilizes Case Based Reasoning methodology for modelling the Web services discovery and matchmaking problem. Our framework uses OWL semantic descriptions extensively for implementing both the components of the CBR engine and the matchmaking profile of the Web services. Publications
A significant proportion of Web resources can be associated to some degree to geo-referenced entities. Statistics collected by search engines and systems on the Web show that spatial information is pervasive on the Web, and that many queries explicitly or implicitly contain spatial factors. Motivated by the requirement of evaluating the closeness between spatial web services, this project experiments a novel approach for integrating some sorts of spatial semantics in CBR case retrieval. The model are tested with web-based travel planning, e.g. flight schedule arrangement, according to user's requests, relevant constraints, and preferences. Publications
Most public image retrieval engines utilise free-text search mechanisms, which often return inaccurate matches as they in principle rely on statistical analysis of query keyword recurrence in the image annotation or surrounding text. In this project we work on creating a semantically-enabled image annotation and retrieval engine that relies on methodically structured ontologies for image annotation, thus allowing for more intelligent reasoning about the image content and subsequently obtaining a more accurate set of results and a richer set of alternatives matchmaking the original query. Our semantic retrieval technology is designed to satisfy the requirements of the commercial image collections market in terms of both accuracy and efficiency of the retrieval process. We also extend our efforts in further improving the recall of our retrieval technology by deploying an efficient query expansion technique. Publications
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