96,563 research outputs found

    Business integration models in the context of web services.

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    E-commerce development and applications have been bringing the Internet to business and marketing and reforming our current business styles and processes. The rapid development of the Web, in particular, the introduction of the semantic web and web service technologies, enables business processes, modeling and management to enter an entirely new stage. Traditional web based business data and transactions can now be analyzed, extracted and modeled to discover new business rules and to form new business strategies, let alone mining the business data in order to classify customers or products. In this paper, we investigate and analyze the business integration models in the context of web services using a micro-payment system because a micro-payment system is considered to be a service intensive activity, where many payment tasks involve different forms of services, such as payment method selection for buyers, security support software, product price comparison, etc. We will use the micro-payment case to discuss and illustrate how the web services approaches support and transform the business process and integration model.

    Ontology-based metrics computation for business process analysis

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    Business Process Management (BPM) aims to support the whole life-cycle necessary to deploy and maintain business processes in organisations. Crucial within the BPM lifecycle is the analysis of deployed processes. Analysing business processes requires computing metrics that can help determining the health of business activities and thus the whole enterprise. However, the degree of automation currently achieved cannot support the level of reactivity and adaptation demanded by businesses. In this paper we argue and show how the use of Semantic Web technologies can increase to an important extent the level of automation for analysing business processes. We present a domain-independent ontological framework for Business Process Analysis (BPA) with support for automatically computing metrics. In particular, we define a set of ontologies for specifying metrics. We describe a domain-independent metrics computation engine that can interpret and compute them. Finally we illustrate and evaluate our approach with a set of general purpose metrics

    Automatic Analysis of Control Flow in Web Services Composition Processes

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    Composition of web services is of great interest to support business-to-business collaboration and provide value added services with desired properties or capabilities. Nevertheless, the standard languages used to create business processes from composite web services lack of formal definition of their semantics and tools to support the analysis of a business process. In this paper we provide a practical approach to formal verification of BPEL4WS executable processes. A syntax-driven operational semantics for BPEL4WS is introduced and an automatic verifier is presented in order to perform a semantic analysis of the flow constructs used in the definition of BPEL4WS processes

    A framework for supporting knowledge representation – an ontological based approach

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    Dissertação para obtenção do Grau de Mestre em Engenharia Electrotécnica e de ComputadoresThe World Wide Web has had a tremendous impact on society and business in just a few years by making information instantly available. During this transition from physical to electronic means for information transport, the content and encoding of information has remained natural language and is only identified by its URL. Today, this is perhaps the most significant obstacle to streamlining business processes via the web. In order that processes may execute without human intervention, knowledge sources, such as documents, must become more machine understandable and must contain other information besides their main contents and URLs. The Semantic Web is a vision of a future web of machine-understandable data. On a machine understandable web, it will be possible for programs to easily determine what knowledge sources are about. This work introduces a conceptual framework and its implementation to support the classification and discovery of knowledge sources, supported by the above vision, where such sources’ information is structured and represented through a mathematical vector that semantically pinpoints the relevance of those knowledge sources within the domain of interest of each user. The presented work also addresses the enrichment of such knowledge representations, using the statistical relevance of keywords based on the classical vector space model concept, and extending it with ontological support, by using concepts and semantic relations, contained in a domain-specific ontology, to enrich knowledge sources’ semantic vectors. Semantic vectors are compared against each other, in order to obtain the similarity between them, and better support end users with knowledge source retrieval capabilities

    Model-driven semantic Web service composition

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    As the number of available Web services increases there is a growing demand to realise complex business processes by combining and reusing available Web services. The reuse and combination of services results in a composition of Web services that may also involve services provided in the Internet. With semantically described Web services, an automated matchmaking of capabilities can help identify suitable services. To address the need for semantically de-fined Web services, OWL-S and WSML have been proposed as competing semantic Web service languages. We show how the proposed semantic Web service languages can be utilized within a model-driven methodology for build-ing composite Web services. In addition we combine the semantic-based discovery with the support for processing QoS requirements to apply a ranking or a selection of the candidates. The methodology describes a process which guides the developer through four phases, starting with the initial modelling, and ending with a new composite service that can be deployed and published to be consumed by other users.

    Aggregation and Adaptation of Web Services

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    Service-oriented computing highly supports the development of future business applications through the use of (Web) services. Two main challenges for Web services are the aggregation of services into new (complex) business applications, and the adaptation of services presenting various types of interaction mismatches. The ultimate objective of this thesis is to define a methodology for the semi-automated aggregation and adaptation of Web services capable of suitably overcoming semantic and behaviour mismatches in view of business process integration within and across organisational boundaries. We tackle the aggregation and adaptation of services described by service contracts, which consist of signature (WSDL), ontology information (OWL), and behaviour specification (YAWL). We first describe an aggregation technique that automatically generates contracts of composite services satisfying (behavioural) client requests from a registry of service contracts. Further on, we present a behaviour-aware adaptation technique that supports the customisation of services to fulfil client requests. The adaptation technique can be used to adapt the behaviour of services to satisfy both functional and behavioural requests. In order to support the generation of service contracts from real-world service descriptions, we also introduce a pattern-based compositional translator for the automated generation of YAWL workflows from BPEL business processes. In this way, we pave the way for the formal analysis, aggregation, and adaptation of BPEL processes

    Decision-enabled dynamic process management for networked enterprises

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    In todays networked economy face numerous information management challenges, both from a process management perspective as well as a decision support perspective. While there have been significant relevant advances in the areas of business process management as well as decision sciences, several open research issues exist. In this paper, we highlight the following key challenges. First, current process modeling and management techniques lack in providing a seamless integration of decision models and tools in existing business processes, which is critical to achieve organizational objectives. Second, given the dynamic nature of business processes in networked enterprises, process management approaches that enable organizations to react to business process changes in an agile manner are required. Third, current state-of-the-art decision model management techniques are not particularly amenable to distributed settings in networked enterprises, which limits the sharing and reuse of models in different contexts, including their utility within managing business processes. In this paper, we present a framework for decision-enabled dynamic process management that addresses these challenges. The framework builds on computational formalisms, including the structured modeling paradigm for representing decision models, and hierarchical task networks from the artificial intelligence (AI) planning area for process modeling. Within the framework, interleaved process planning (modeling), execution and monitoring for dynamic process management throughout the process lifecycle is proposed. A service-oriented architecture combined with advances from the semantic Web field for model management support within business processes is proposed

    AI-based component management system for structured content creation, annotation, and publication

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    Nowadays, the ever changing and growing amount of information, regulations, and data requires large organizations to describe on the web increasingly complex and interdependent business processes and services, ideally creating user-profiled content that is clear and up to date. To successfully achieve this goal, as off-the-shelf solutions are missing, institutions have to embark in a digital transformation process fully endorsed by governance, led by a multidisciplinary team of experts, and strongly integrated with artificial intelligence (AI) tools. In this paper we describe how a content service platform, that integrates human processes and state-of-the-art AI services, was successfully employed in our institution (UniGe) to manage, and support a system of about 200 websites. Following a single-sourcing paradigm, its advent allowed for the decoupling of content and technology, preparing UniGe for the future needs of the semantic web

    Semantics take the SOA registry to the next level: an empirical study in a telecom company

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    We describe an empirical study of the creation of a Semantic Service Registry in the context of the Operations Support Systems (OSS) department of a telecom company, to address an emerging problem of finding the right services to build new business processes in a pool that steadily increases. We show how to obtain an ontology for the telecom domain to annotate services and thus benefit from semantic technologies to effectively find them based on description logics inference mapping. We designed and implemented a proof of concept for providing a matching degree even when the cardinality of the service elements of the query and the cardinality of the service elements being sought differ. This is relevant for web services reusability and flexibility. Our solutions are overviewed and a set of lessons learned are discussed
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