Automated semantic web service composition is one of the critical research challenges of service-oriented computing, since it allows users to create an application simply by specifying the inputs that the application requires, the outputs it should produce, and any constraints it should respect. The composition problem has been handled using a variety of techniques, from Artificial Intelligence (AI) planning to optimization algorithms. However no approach so far has focused on handling three composition dimensions simul

In this research, a new evaluation model to choose adequate ontology that fit user requirements is proposed. The proposed model presents two main features distinct from previous research models: First, it enables users to select from a set of proposed metrics, those who they help in the ontology evaluation process; and to assign weights to each one based on assumed impacts on this process. Second, it enables users to evaluate locally stored ontologies, and/or request search engines for available ontologies. The main goal of this model is to ease the ontology evaluation task, for users wishing to reuse available ontologies, enabling them to choose the more adequate ontology to their requirements.

Abstract-The first phase of reverse engineering of weboriented applications is the extraction of concepts hidden in HTML pages including tables, lists and forms, or marked in XML documents. In this paper, we present an approach to index semantically these two sources of information (HTML page and XML document) using on the one hand, domain ontology to validate the extracted concepts and on the other hand the similarity measurement between ontology concepts with the aim of enrichment the index. This approach will be conceived in three steps (modeling, attaching and Enrichment) and thereafter, it will be realized and implemented by examples. The obtained results lead to better re-engineering of web applications and subsequently a distinguished improvement in the web structuring.

Abstract-Recommender systems have shown great potential to help users find interesting and relevant Web service (WS) from within large registers. However, with the proliferation of WSs, recommendation becomes a very difficult task. Social computing seems offering innovative solutions to overcome those shortcomings. Social computing is at the crossroad of computer sciences and social sciences disciplines by looking into ways of improving application design and development using elements that people encounter daily such as social networks, trust, reputation, and recommendation. In this paper, we propose a social trust-aware system for recommending Web services (WSs) based on social qualities of WSs that they exhibit towards peers at runtime, and trustworthiness of the users who provide feedback on their overall experience using WSs. A set of experiments to assess the fairness and accuracy of the proposed system are reported in the paper, showing promising results and demonstrating that our service recommendation method significantly outperforms conventional similarity-based and trust-based service recommendation methods.

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Semantic similarity calculation models are found in many applications, with the aim to give additional knowledge to reason about their data. The choice of a similarity measure is quite crucial for a successful implementation of reasoning. In this work, we present an update of similarity calculation presented by Wu and Palmer which is considered the fastest in time generation of similarity. The results obtained show that the measure produced provides a significant improvement in the relevance of the values produced for the similarity of two concepts in ontology.

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Business process modeling notation (BPMN) is a widely used business model process. The importance of security is apparent, but traditionally, it is considered after the business processes definition. There is a need for integrated tools and a methodology that allows for specifying and enforcing compliance and security requirements for business process-driven enterprise systems. Therefore, it is very important to capture the security requirements at conceptual stage in order to identify the security needs. BPMN is lacking the ability to model and present security concepts. This will increase the vulnerability of the system and make the future development of security for the system more difficult. This article proposes a novel extension to BPMN notation based on cyber security ontologies. The authors incorporate visual constructs for modeling security requirements. In order to provide a commonly usable extension, these enhancements were implemented as BPMN metamodel extension. The authors illustrate capabilities and benefits of extension with a real-life example.