Preface: Semantic Web technologies for mobile and pervasive environments

Artificial Intelligence provides a rich set of methods and tools for implementing the Ambient Intelligence vision, i.e. to transform our environments into smart spaces assisting as with our everyday tasks in an intelligent, seamless and non-obtrusive way. Among them, Semantic Web technologies, such as RDF, ontology languages and others, can be used to address several of the challenges that come with this vision, mainly with respect to modelling, sharing and reasoning with context information. This thematic issue demonstrates their capabilities by presenting three different Semantic Web-based solutions for mobile and computing environments

Object-Oriented Similarity Measures for Semantic Web Service Matchmaking

The semantic annotation of Web services capabilities with ontological information aims at providing the neces-sary infrastructure for facilitating efficient and accurate service discovery. The main idea is to apply reasoning techniques over semantically enhanced Web service re-quests and advertisements in order to determine Web ser-vices that meet certain requirements. In this paper we present our work for introducing similarity measures in-spired from the domain of Object-Oriented paradigm for ontology concept matching. Our work focuses on the utili-zation of such measures over an Object-Oriented schema that is created through mapping rules of OWL constructs and semantics into the Object-Oriented model. The goal of the approach is to combine the Object-Oriented repre-sentation of the information and the reasoning over OWL semantics in order to enhance the retrieval of semanti-cally relevant, to some criteria, Web services

Ontology-based personalized job recommendation framework for migrants and refugees

Participation in the labor market is seen as the most important factor favoring long-term integration of migrants and refugees into society. This paper describes the job recommendation framework of the Integration of Migrants MatchER SErvice (IMMERSE). The proposed framework acts as a matching tool that enables the contexts of individual migrants and refugees, including their expectations, languages, educational background, previous job experience and skills, to be captured in the ontology and facilitate their matching with the job opportunities available in their host country. Profile information and job listings are processed in real time in the back-end, and matches are revealed in the front-end. Moreover, the matching tool considers the activity of the users on the platform to provide recommendations based on the similarity among existing jobs that they already showed interest in and new jobs posted on the platform. Finally, the framework takes into account the location of the users to rank the results and only shows the most relevant location-based recommendation

On the Combination of Textual and Semantic Descriptions for Automated Semantic Web Service Classification

Abstract Semantic Web services have emerged as the solution to the need for automating several aspects related to service-oriented architectures, such as service discovery and composition, and they are realized by combining Semantic Web technologies and Web service standards. In the present paper, we tackle the problem of automated classification of Web services according to their application domain taking into account both the textual description and the semantic annotations of OWL-S advertisements. We present results that we obtained by applying machine learning algorithms on textual and semantic descriptions separately and we propose methods for increasing the overall classification accuracy through an extended feature vector and an ensemble of classifiers

Towards Semantic Detection of Smells in Cloud Infrastructure Code

Automated deployment and management of Cloud applications relies on descriptions of their deployment topologies, often referred to as Infrastructure Code. As the complexity of applications and their deployment models increases, developers inadvertently introduce software smells to such code specifications, for instance, violations of good coding practices, modular structure, and more. This paper presents a knowledge-driven approach enabling developers to identify the aforementioned smells in deployment descriptions. We detect smells with SPARQL-based rules over pattern-based OWL 2 knowledge graphs capturing deployment models. We show the feasibility of our approach with a prototype and three case studies.Comment: 5 pages, 6 figures. The 10 th International Conference on Web Intelligence, Mining and Semantics (WIMS 2020

Semantic Web Service Composition using Planning and Ontology Concept Relevance

Abstract: This paper presents PORSCE II, a system that combines planning and ontology concept relevance for automatically composing semantic web services. The presented approach includes transformation of the web service composition problem into a planning problem, enhancement with semantic awareness and relaxation and solution through external planners. The produced plans are visualized and their accuracy is assessed

Implementation of an Interactive Crowd-Enhanced Content Management System for Tourism Development

This paper investigated the role of interactive tourist mobile apps in tourism development. The researchers presented the e-Tracer application, which was developed taking into consideration the recent advantages in mobile computing, the importance of user-generated content and the needs of northern Greece and the lower Balkan countries. Apart from crowd-based content creation, a new generation of apps for tourism development may include additional components like serious games for tourists, map-based navigation systems and augmented/virtual reality applications, in order to offer memorable user experiences for tourists. An agile content management system design methodology was followed by taking into account the needs of alternative tourist destinations, small to medium sized real-world museums and driver rest areas located around highways which connect cross-country destinations in the lower Balkan countries and Turkey. This work positioned the role of interactive crowd-enhanced platforms for content management of tourist-related information in tourism development, economic growth and sustainability of the Egnatia motorway surrounding areas in Greece. Keywords: mobile computing, content management systems, recommender systems, serious games, virtual/augmented reality, tourism developmen

SODALITE@RT: Orchestrating Applications on Cloud-Edge Infrastructures

AbstractIoT-based applications need to be dynamically orchestrated on cloud-edge infrastructures for reasons such as performance, regulations, or cost. In this context, a crucial problem is facilitating the work of DevOps teams in deploying, monitoring, and managing such applications by providing necessary tools and platforms. The SODALITE@RT open-source framework aims at addressing this scenario. In this paper, we present the main features of the SODALITE@RT: modeling of cloud-edge resources and applications using open standards and infrastructural code, and automated deployment, monitoring, and management of the applications in the target infrastructures based on such models. The capabilities of the SODALITE@RT are demonstrated through a relevant case study