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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 had

Large parts of today's data is stored in text documents that undergo a series of changes during their lifetime. For instance during the development of a software product the source code changes frequently. Currently, managing such data relies on version control systems (VCSs). Extracting information from large documents and their different versions is a manual and tedious process. We present Qvestor, a system that allows to declaratively query documents. It leverages information about the structure of a document that is available as a context-free grammar and allows to declaratively query document versions through a grammar annotated with relational algebra expressions. We define and illustrate the annotation of grammars with relational algebra expressions and show how to translate the annotations to easy to use SQL views.

This paper describes a sentence ranking technique using entropy measures, in a multi-document unstructured text summarization application. The method is topic specific and makes use of a simple language independent training framework to calculate entropies of symbol units. The document set is summarized by assigning entropy-based scores to a reduced set of sentences obtained using a graph representation for sentence similarity. The performance is seen to be better than some of the common statistical techniques, when applied on the same data set. Commonly used measures like precision, recall and f-score have been modified and used as a new set of measures for comparing the performance of summarizers. The rationale behind such a modification is also presented. Experimental results are presented to illustrate the relevance of this method in cases where it is difficult to have language specific dictionaries, translators and document-summary pairs for training.

For autonomously developed information systems to interoperate in a meaningful manner, ontologies capturing the intended semantics of that interoperation have to be developed by a community of stakeholders in those information systems. As the requirements of the ontology and the ontology itself evolve, so in general will the community, and vice versa. Ontology construction should thus be viewed as a complex activity leading to formalized semantic agreement involving various social processes within the community, and that may translate into a number of ontology evolution operators to be implemented. The hybrid ontologies that emerge in this way indeed need to support both the social agreement processes in the stakeholder communities and the eventual reasoning implemented in the information systems that are governed by these ontologies. In this paper, we discuss formal aspects of the social processes involved, a so-called fact-oriented methodology and formalism to structure and describe these, as well as certain relevant aspects of the communities in which they occur. We also report on a prototypical tool set that supports such a methodology, and on examples of some early experiments.