Building Service Compositions Based on data on Use of Services by Users

The automatic service composition is discussed in the article. The method is proposed for building the service composition based on the processing of statistical data on individual applying services (tasks) by users. The method is based on linking tasks to each other, determining data dependencies, parameters of services whose values are rigidly set by the composition of services, and parameters whose values can be changed by the user are highlighted. Service compositions are built in the form of a directed graph of DAG. The methods have been developed for reducing the set of obtained service compositions, which allow us to highlight useful ones and rank them by degree of use. In particular, equivalent service compositions based on isomorphism of DAG graphs are determined, trivial ones are discarded, and only compositions that lead to the published result are left behind.

Enriching Web Services Tags to Improve Data-Driven Web Services Composition

Due to the large number of existing services and complexity of manual composition, automatic service composition is provided to enable automatic search of the service compositions for the given queries. Many solutions for automatic service composition have been developed, including integer programming, graph planning, artificial intelligence, and so on in this paper, a heuristic method is proposed to improve the data-driven composition of web services by enriching tags based on tags semantic. To do so, firstly, useful information on web services is collected from various sources and is turned into collections of tags. In the next step, using the hierarchical clustering algorithm, the tags are clustered based on semantic similarity. Thereafter, for services which do not have enough tags, enrichment of the tag is carried out and finally, using an algorithm, composition solutions based on QoS parameters are extracted, which can formulate user targets or even provide potential compositions. Moreover, a series of tests were conducted on the web services, which validate the efficiency of the proposed approach. The experimental results confirm the effectiveness of the proposed service composition method and high quality of tag enriching strategies.

Ontology-Based Human-Computer Cloud for Decision Support

A variety of information processing and decision support tasks (especially in the context of smart city or smart tourist destination) rely both on the automated and human-based procedures. The article proposes a multi-layer cloud environment that, first, unifies various kinds of resources used by these information processing and decision-support scenarios (hardware, software, and human), and second, implements an ontology-based automatic service composition procedures that can be used to build ad hoc decision-support services for problems unknown in advance. The service composition is based on uniform description of all parts of the environment with a help of ontologies. The article describes the architecture and models of the novel human-computer cloud environment. It also describes several scenarios of decision support in tourism leveraging the proposed human-computer cloud concept.

Semantically Enhanced Web Service for Global Supply Chain Disruption Management

The recent coronavirus pandemic has now unleashed a global supply chain crisis across a huge number of organizations, stemming from a lack of understanding and flexibility of the multiple layers of their global supply chains and a lack of diversification in their sourcing strategies. One of the technical options to mitigate the pandemic is to automate business processes by which heterogeneous data integration is encouraged. The convergence of Semantic Web with service-oriented computing is manifested by Semantic Web services technology. It addresses the major challenge of automated, interoperable, and meaningful coordination of web service composition in industrial applications – such as apparel business. Automatic service composition may dramatically improve the development efficiency of web service applications. This chapter proposes an approach to automatically process semantic service composition (SSC) using description logics (DLs) to provide well-defined semantics. Also, this chapter explains the role of ontologies in the architecture of the Semantic Web.