Hybrid focused crawling on the Surface and the Dark Web

Focused crawlers enable the automatic discovery of Web resources about a given topic by automatically navigating through the Web link structure and selecting the hyperlinks to follow by estimating their relevance to the topic of interest. This work proposes a generic focused crawling framework for discovering resources on any given topic that reside on the Surface or the Dark Web. The proposed crawler is able to seamlessly navigate through the Surface Web and several darknets present in the Dark Web (i.e., Tor, I2P, and Freenet) during a single crawl by automatically adapting its crawling behavior and its classifier-guided hyperlink selection strategy based on the destination network type and the strength of the local evidence present in the vicinity of a hyperlink. It investigates 11 hyperlink selection methods, among which a novel strategy proposed based on the dynamic linear combination of a link-based and a parent Web page classifier. This hybrid focused crawler is demonstrated for the discovery of Web resources containing recipes for producing homemade explosives. The evaluation experiments indicate the effectiveness of the proposed focused crawler both for the Surface and the Dark Web

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

Deploying Semantic Web Technologies for Information Fusion of Terrorism-related Content and Threat Detection on the Web

The Web and social media nowadays play an increasingly significant role in spreading terrorism-related propaganda and content. In order to deploy counterterrorism measures, authorities rely on automated systems for analysing text, multimedia, and social media content on the Web. However, since each of these systems is an isolated solution, investigators often face the challenge of having to cope with a diverse array of heterogeneous sources and formats that generate vast volumes of data. Semantic Web technologies can alleviate this problem by delivering a toolset of mechanisms for knowledge representation, information fusion, semantic search, and sophisticated analyses of terrorist networks and spatiotemporal information. In the Semantic Web environment, ontologies play a key role by offering a shared, uniform model for semantically integrating information from multimodal heterogeneous sources. An additional benefit is that ontologies can be augmented with powerful tools for semantic enrichment and reasoning. This paper presents such a unified semantic infrastructure for information fusion of terrorism-related content and threat detection on theWeb. The framework is deployed within the TENSOR EU-funded project, and consists of an ontology and an adaptable semantic reasoning mechanism. We strongly believe that, in the short- and long-term, these techniques can greatly assist Law Enforcement Agencies in their investigational operations

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

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

TENSOR: retrieval and analysis of heterogeneous online content for terrorist activity recognition

The proliferation of terrorist generated content online is a cause for concern as it goes together with the rise of radicalisation and violent extremism. Law enforcement agencies (LEAs) need powerful platforms to help stem the influence of such content. This article showcases the TENSOR project which focusses on the early detection of online terrorist activities, radicalisation and recruitment. Operating under the H2020 Secure Societies Challenge, TENSOR aims to develop a terrorism intelligence platform for increasing the ability of LEAs to identify, gather and analyse terrorism-related online content. The mechanisms to tackle this challenge by bringing together LEAs, industry, research, and legal experts are presented

A Technological Framework for the Authoring and Presentation of T-learning Courses

Broadcasting interactive learning applications through the digital TV promises to open new pedagogical perspectives, also in a life-long learning perspective, given the wide penetration of the medium. This article proposes an open flexible and composable framework for the development, the delivery and the presentation of t-learning courses in interactive digital TV (iDTV). The framework is divided into two main parts: the production side, where the course is prepared and the client side, where it is presented on iDTV, and where the user can perform the educational interaction. The course production is supported by an ad-hoc designed authoring tool, while the runtime user interaction on iDTV is managed by a multimedia course player providing personalization services and a library of educational and entertainment elements and services. Seven experimental t-learning courses were created by pedagogical experts in several knowledge domains and served as an important test and evaluation bench for the framework, in view of the upcoming extensive end-user testing

MindSpaces:Art-driven Adaptive Outdoors and Indoors Design

MindSpaces provides solutions for creating functionally and emotionally appealing architectural designs in urban spaces. Social media services, physiological sensing devices and video cameras provide data from sensing environments. State-of-the-Art technology including VR, 3D design tools, emotion extraction, visual behaviour analysis, and textual analysis will be incorporated in MindSpaces platform for analysing data and adapting the design of spaces.</p

Addressing Challenges in Long-Term Strategic Energy Planning in LMICs: Learning Pathways in an Energy Planning Ecosystem

This paper presents an innovative approach to addressing critical global challenges in long-term energy planning for low- and middle-income countries (LMICs). The paper proposes and tests an international enabling environment, a delivery ecosystem, and a community of practice. These components are integrated into workflows that yield four self-sustaining capacity-development outcomes. Planning long-term energy strategies in LMICs is particularly challenging due to limited national agency and poor international coordination. While outsourcing energy planning to foreign experts may appear to be a viable solution, it can lead to a reduction in government agency (the ability of a government to make its own informed analysis and decisions). Additionally, studies commissioned by external experts may have conflicting terms of reference, and a lack of familiarity with local conditions can result in misrepresentations of on-the-ground realities. It is argued here that enhancing national agency and analytical capacity can improve coordination and lead to more robust planning across line ministries and technical assistance (TA) providers. Moreover, the prevailing consulting model hampers the release and accessibility of underlying analytics, making it difficult to retrieve, reuse, and reconstruct consultant outputs. The absence of interoperability among outputs from various consultants hinders the ability to combine and audit the insights they provide. To overcome these challenges, five strategic principles for energy planning in LMICs have been introduced and developed in collaboration with 21 international and research organizations, including the AfDB, IEA, IRENA, IAEA, UNDP, UNECA, the World Bank, and WRI. These principles prioritize national ownership, coherence and inclusivity, capacity, robustness, transparency and accessibility. In this enabling environment, a unique delivery ecosystem consisting of knowledge products and activities is established. The paper focuses on two key knowledge products as examples of this ecosystem: the open-source energy modeling system (OSeMOSYS) and the power system flexibility tool (IRENA FlexTool). These ecosystem elements are designed to meet user-friendliness, retrievability, reusability, reconstructability, repeatability, interoperability, and audibility (U4RIA) goals. To ensure the sustainability of this ecosystem, OpTIMUS is introduced—a community of practice dedicated to maintaining, supporting, expanding, and nurturing the elements within the ecosystem. Among other ecosystem elements, training and research initiatives are introduced, namely the Energy Modelling Platform for Africa, Latin America and the Caribbean, and Asia-Pacific as well as the ICTP Joint Summer School on Modelling Tools for Sustainable Development. Once deployed via workflows, the preliminary outcomes of these capacity-development learning pathways show promise. Further investigation is necessary to evaluate their long-term impacts, scalability, replication, and deployment costs