Scalable Data Integration for Linked Data

Linked Data describes an extensive set of structured but heterogeneous datasources where entities are connected by formal semantic descriptions. In thevision of the Semantic Web, these semantic links are extended towards theWorld Wide Web to provide as much machine-readable data as possible forsearch queries. The resulting connections allow an automatic evaluation to findnew insights into the data. Identifying these semantic connections betweentwo data sources with automatic approaches is called link discovery. We derivecommon requirements and a generic link discovery workflow based on similaritiesbetween entity properties and associated properties of ontology concepts. Mostof the existing link discovery approaches disregard the fact that in times ofBig Data, an increasing volume of data sources poses new demands on linkdiscovery. In particular, the problem of complex and time-consuming linkdetermination escalates with an increasing number of intersecting data sources.To overcome the restriction of pairwise linking of entities, holistic clusteringapproaches are needed to link equivalent entities of multiple data sources toconstruct integrated knowledge bases. In this context, the focus on efficiencyand scalability is essential. For example, reusing existing links or backgroundinformation can help to avoid redundant calculations. However, when dealingwith multiple data sources, additional data quality problems must also be dealtwith. This dissertation addresses these comprehensive challenges by designingholistic linking and clustering approaches that enable reuse of existing links.Unlike previous systems, we execute the complete data integration workflowvia a distributed processing system. At first, the LinkLion portal will beintroduced to provide existing links for new applications. These links act asa basis for a physical data integration process to create a unified representationfor equivalent entities from many data sources. We then propose a holisticclustering approach to form consolidated clusters for same real-world entitiesfrom many different sources. At the same time, we exploit the semantic typeof entities to improve the quality of the result. The process identifies errorsin existing links and can find numerous additional links. Additionally, theentity clustering has to react to the high dynamics of the data. In particular,this requires scalable approaches for continuously growing data sources withmany entities as well as additional new sources. Previous entity clusteringapproaches are mostly static, focusing on the one-time linking and clustering ofentities from few sources. Therefore, we propose and evaluate new approaches for incremental entity clustering that supports the continuous addition of newentities and data sources. To cope with the ever-increasing number of LinkedData sources, efficient and scalable methods based on distributed processingsystems are required. Thus we propose distributed holistic approaches to linkmany data sources based on a clustering of entities that represent the samereal-world object. The implementation is realized on Apache Flink. In contrastto previous approaches, we utilize efficiency-enhancing optimizations for bothdistributed static and dynamic clustering. An extensive comparative evaluationof the proposed approaches with various distributed clustering strategies showshigh effectiveness for datasets from multiple domains as well as scalability on amulti-machine Apache Flink cluster

Semantic hyper/multimedia adaptation: schemes and applications

Nowadays, more and more users are witnessing the impact of Hypermedia/ Multimedia as well as the penetration of social applications in their life. Internet was designed in order maximize user choice and innovation, while Web, as the ultimate service over thismulti-layered structure, created a global software environment for millions of users worldwide. Both technological attainments are continuously revolutionizing the way we process, use, exchange and disseminate information. Through this revolution, many real-life applications in the fields of communication, commerce, education, government, and entertainment are redefined. Parallel to the evolution of Internet and Web, several Hypermedia/Multimedia schemes and technologies bring semantic-based intelligent, personalized and adaptive services to the end users. More and more techniques are applied in media systems in order to be user/group-centric, adapting to different content and context features of a single or a community user. In respect to all the above, researchers need to explore and study the plethora of challenges that emergent personalisation and adaptation technologies bring to the new era. This edited volume aims to increase the awareness of researchers in this area. It includes thirteen (13) articles authored by researchers from eight (8) different European countries, namely Belgium, Cyprus, Czech Republic, Greece, Italy, Slovakia, Spain, and UK. All accepted contributions provide an in-depth investigation on research and deployment issues, regarding already introduced schemes and applications in Semantic Hyper/Multimedia and Social Media Adaptation. Moreover, the authors provide survey-based articles, so as potential readers can use it for catching up the recent trends and applications in respect to the relevant literature. Finally, the authors discuss and present their approach in the respective field or problem addressed. For consistency purposes and in order to further highlight the authors’ contributions, we divided this edited volume to four (4) separate chapters, which cover most of the topics announced in our open call for papers. The chapter titles are: – Chapter 1: Semantics Acquisition and Usage, – Chapter 2: Reasoning for Personalization and Recommendation, – Chapter 3: Social and Context-aware Adaptation, and – Chapter 4: Multimedia and Open Standards The reader can also find analytical prefaces of each chapter, which summarise the aims of each article, and how the work described is related with the chapter topic. From our part, as Guest-Editors, we would like to thank all authors for their submitted contributions and the opportunity they gave us to edit this volume. We hope that all the contributions that appear in this edited volume will contribute towards a deeper understanding of the key problems in this area, and that they will help researchers and developers to find new solutions to existing problems, opening in parallel new research paths in related topics. We also would like to explicitly acknowledge the help of all referees involved during the review phases. Their valuable comments and suggestions improved the quality of the published works. Last but not least, we would like to express our gratitude to Prof. Dr. Janusz Kacprzyk, and Dr. Thomas Ditzinger, Editor and Senior Editor of Springer SCI book series respectively, for the all the support and guidance provided to us, as well as, the fruitful cooperation we ha

Editorial on "semantic hyper/multimedia adaptation: Schemes and applications"

Nowadays, more and more users are witnessing the impact of Hypermedia/Multimedia as well as the penetration of social applications in their life. Parallel to the evolution of the Internet and Web, several Hypermedia/Multimedia schemes and technologies bring semantic-based intelligent, personalized and adaptive services to the end users. More and more techniques are applied in media systems in order to be user/group-centric, adapting to different content and context features of a single or a community user. In respect to all the above, researchers need to explore and study the plethora of challenges that emergent personalisation and adaptation technologies bring to the new era. This edited volume aims to increase the awareness of researchers in this area. All contributions provide an in-depth investigation on research and deployment issues, regarding already introduced schemes and applications in Semantic Hyper/Multimedia and Social Media Adaptation. Moreover, the authors provide survey-based articles, so as potential readers can use it for catching up the recent trends and applications in respect to the relevant literature. Finally, the authors discuss and present their approach in the respective field or problem addressed