Search (13 results, page 1 of 1)

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Content

Winfried Gödert: Programmatic Issues and Introduction - Dagobert Soergel: Conceptual Foundations for Semantic Mapping and Semantic Search - Jan-Helge Jacobs, Tina Mengel, Katrin Müller: Insights and Outlooks: A Retrospective View on the CrissCross Project - Yvonne Jahns, Helga Karg: Translingual Retrieval: Moving between Vocabularies - MACS 2010 - Jessica Hubrich: Intersystem Relations: Characteristics and Functionalities - Stella G Dextre Clarke: In Pursuit of Interoperability: Can We Standardize Mapping Types? - Philipp Mayr, Philipp Schaer, Peter Mutschke: A Science Model Driven Retrieval Prototype - Claudia Effenberger, Julia Hauser: Would an Explicit Versioning of the DDC Bring Advantages for Retrieval? - Gordon Dunsire: Interoperability and Semantics in RDF Representations of FRBR, FRAD and FRSAD - Maja Zumer: FRSAD: Challenges of Modeling the Aboutness - Michael Panzer: Two Tales of a Concept: Aligning FRSAD with SKOS - Felix Boteram: Integrating Semantic Interoperability into FRSAD

Date

22. 2.2013 11:34:18

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Abstract

Ontologies are viewed as the silver bullet for many applications, but in open or evolving systems, different parties can adopt different ontologies. This increases heterogeneity problems rather than reducing heterogeneity. This book proposes ontology matching as a solution to the problem of semantic heterogeneity, offering researchers and practitioners a uniform framework of reference to currently available work. The techniques presented apply to database schema matching, catalog integration, XML schema matching and more. Ontologies tend to be found everywhere. They are viewed as the silver bullet for many applications, such as database integration, peer-to-peer systems, e-commerce, semantic web services, or social networks. However, in open or evolving systems, such as the semantic web, different parties would, in general, adopt different ontologies. Thus, merely using ontologies, like using XML, does not reduce heterogeneity: it just raises heterogeneity problems to a higher level. Euzenat and Shvaiko's book is devoted to ontology matching as a solution to the semantic heterogeneity problem faced by computer systems. Ontology matching aims at finding correspondences between semantically related entities of different ontologies. These correspondences may stand for equivalence as well as other relations, such as consequence, subsumption, or disjointness, between ontology entities. Many different matching solutions have been proposed so far from various viewpoints, e.g., databases, information systems, artificial intelligence. With Ontology Matching, researchers and practitioners will find a reference book which presents currently available work in a uniform framework. In particular, the work and the techniques presented in this book can equally be applied to database schema matching, catalog integration, XML schema matching and other related problems. The objectives of the book include presenting (i) the state of the art and (ii) the latest research results in ontology matching by providing a detailed account of matching techniques and matching systems in a systematic way from theoretical, practical and application perspectives.

Date

20. 6.2012 19:08:22

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Abstract

The modern Web has grown from a publishing place of well-structured data and HTML pages for companies and experienced users into a vivid publishing and data exchange community in which everyone can participate, both as a data consumer and as a data producer. Unavoidably, the data available on the Web became highly heterogeneous, ranging from highly structured and semistructured to highly unstructured user-generated content, reflecting different perspectives and structuring principles. The full potential of such data can only be realized by combining information from multiple sources. For instance, the knowledge that is typically embedded in monolithic applications can be outsourced and, thus, used also in other applications. Numerous systems nowadays are already actively utilizing existing content from various sources such as WordNet or Wikipedia. Some well-known examples of such systems include DBpedia, Freebase, Spock, and DBLife. A major challenge during combining and querying information from multiple heterogeneous sources is entity linkage, i.e., the ability to detect whether two pieces of information correspond to the same real-world object. This chapter introduces a novel approach for addressing the entity linkage problem for heterogeneous, uncertain, and volatile data.

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Abstract

Social tagging, hashtags, and geotags are used across a variety of platforms (Twitter, Facebook, Tumblr, WordPress, Instagram) in different countries and cultures. This book, representing researchers and practitioners across different information professions, explores how social tags can link content across a variety of environments. Most studies of social tagging have tended to focus on applications like library catalogs, blogs, and social bookmarking sites. This book, in setting out a theoretical background and the use of a series of case studies, explores the role of hashtags as a form of linked data?without the complex implementation of RDF and other Semantic Web technologies.

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Abstract

Linked Open Data initiative has played a vital role in the realization of the Semantic Web at a global scale by publishing and interlinking diverse data sources on the Web. Access to this huge amount of Linked Data presents exciting benefits and opportunities. However, the inherent complexity attached to Linked Data understanding, lack of potential use cases and applications which can consume Linked Data hinders its full exploitation by naïve web users and developers. This book aims to address these core limitations of Linked Open Data and contributes by presenting: (i) Conceptual model for fundamental understanding of Linked Open Data sphere, (ii) Linked Data application to search, consume and aggregate various Linked Data resources, (iii) Semantification and interlinking technique for conversion of legacy data, and (iv) Potential application areas of Linked Open Data.

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Abstract

Today's complex, information-intensive problems often require people to work together. Mostly these tasks go far beyond simply searching together; they include information lookup, sharing, synthesis, and decision-making. In addition, they all have an end-goal that is mutually beneficial to all parties involved. Such "collaborative information seeking" (CIS) projects typically last several sessions and the participants all share an intention to contribute and benefit. Not surprisingly, these processes are highly interactive. Shah focuses on two individually well-understood notions: collaboration and information seeking, with the goal of bringing them together to show how it is a natural tendency for humans to work together on complex tasks. The first part of his book introduces the general notions of collaboration and information seeking, as well as related concepts, terminology, and frameworks; and thus provides the reader with a comprehensive treatment of the concepts underlying CIS. The second part of the book details CIS as a standalone domain. A series of frameworks, theories, and models are introduced to provide a conceptual basis for CIS. The final part describes several systems and applications of CIS, along with their broader implications on other fields such as computer-supported cooperative work (CSCW) and human-computer interaction (HCI). With this first comprehensive overview of an exciting new research field, Shah delivers to graduate students and researchers in academia and industry an encompassing description of the technologies involved, state-of-the-art results, and open challenges as well as research opportunities.

Content

Inhalt: Part I Introduction.- Introduction.- Collaboration.- Collaborative Information Seeking (CIS) in Context.- Part II Conceptual Understanding of CIS.- Frameworks for CIS Research and Development.- Toward a Model for CIS.- Part III CIS Systems, Applications, and Implications.- Systems and Tools for CIS.- Evaluation.- Conclusion.- Ten Stories of Five Cs.- Brief Overview of Computer-Supported Cooperative Work (CSCW).- Brief Overview of Computer-Supported Collaborative Learning (CSCL).- Brief Overview of Computer-Mediated Communication (CMC).

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Abstract

This highly practical handbook teaches you how to unlock the value of your existing metadata through cleaning, reconciliation, enrichment and linking and how to streamline the process of new metadata creation. Libraries, archives and museums are facing up to the challenge of providing access to fast growing collections whilst managing cuts to budgets. Key to this is the creation, linking and publishing of good quality metadata as Linked Data that will allow their collections to be discovered, accessed and disseminated in a sustainable manner. This highly practical handbook teaches you how to unlock the value of your existing metadata through cleaning, reconciliation, enrichment and linking and how to streamline the process of new metadata creation. Metadata experts Seth van Hooland and Ruben Verborgh introduce the key concepts of metadata standards and Linked Data and how they can be practically applied to existing metadata, giving readers the tools and understanding to achieve maximum results with limited resources. Readers will learn how to critically assess and use (semi-)automated methods of managing metadata through hands-on exercises within the book and on the accompanying website. Each chapter is built around a case study from institutions around the world, demonstrating how freely available tools are being successfully used in different metadata contexts. This handbook delivers the necessary conceptual and practical understanding to empower practitioners to make the right decisions when making their organisations resources accessible on the Web. Key topics include, the value of metadata; metadata creation - architecture, data models and standards; metadata cleaning; metadata reconciliation; metadata enrichment through Linked Data and named-entity recognition; importing and exporting metadata; ensuring a sustainable publishing model. This will be an invaluable guide for metadata practitioners and researchers within all cultural heritage contexts, from library cataloguers and archivists to museum curatorial staff. It will also be of interest to students and academics within information science and digital humanities fields. IT managers with responsibility for information systems, as well as strategy heads and budget holders, at cultural heritage organisations, will find this a valuable decision-making aid.

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Abstract

This collection of research papers provides extensive information on deploying services, concepts, and approaches for using open linked data from libraries and other cultural heritage institutions. With a special emphasis on how libraries and other cultural heritage institutions can create effective end user interfaces using open, linked data or other datasets. These papers are essential reading for any one interesting in user interface design or the semantic web.

Content

H. Frank Cervone: Linked data and user interaction : an introduction -- Paola Di Maio: Linked Data Beyond Libraries Towards Universal Interfaces and Knowledge Unification -- Emmanuelle Bermes: Following the user's flow in the Digital Pompidou -- Patrick Le Bceuf: Customized OPACs on the Semantic Web : the OpenCat prototype -- Ryan Shaw, Patrick Golden and Michael Buckland: Using linked library data in working research notes -- Timm Heuss, Bernhard Humm.Tilman Deuschel, Torsten Frohlich, Thomas Herth and Oliver Mitesser: Semantically guided, situation-aware literature research -- Niklas Lindstrom and Martin Malmsten: Building interfaces on a networked graph -- Natasha Simons, Arve Solland and Jan Hettenhausen: Griffith Research Hub. Vgl.: http://d-nb.info/1032799889.

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Content

Neumaier, Sebastian (et al.): Data Integration for Open Data on the Web - Stamou, Giorgos (et al.): Ontological Query Answering over Semantic Data - Calì, Andrea: Ontology Querying: Datalog Strikes Back - Sequeda, Juan F.: Integrating Relational Databases with the Semantic Web: A Reflection - Rousset, Marie-Christine (et al.): Datalog Revisited for Reasoning in Linked Data - Kaminski, Roland (et al.): A Tutorial on Hybrid Answer Set Solving with clingo - Eiter, Thomas (et al.): Answer Set Programming with External Source Access - Lukasiewicz, Thomas: Uncertainty Reasoning for the Semantic Web - Calvanese, Diego (et al.): OBDA for Log Extraction in Process Mining

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Abstract

The Web has become the world's largest database, with search being the main tool that allows organizations and individuals to exploit its huge amount of information. Search on the Web has been traditionally based on textual and structural similarities, ignoring to a large degree the semantic dimension, i.e., understanding the meaning of the query and of the document content. Combining search and semantics gives birth to the idea of semantic search. Traditional search engines have already advertised some semantic dimensions. Some of them, for instance, can enhance their generated result sets with documents that are semantically related to the query terms even though they may not include these terms. Nevertheless, the exploitation of the semantic search has not yet reached its full potential. In this book, Roberto De Virgilio, Francesco Guerra and Yannis Velegrakis present an extensive overview of the work done in Semantic Search and other related areas. They explore different technologies and solutions in depth, making their collection a valuable and stimulating reading for both academic and industrial researchers. The book is divided into three parts. The first introduces the readers to the basic notions of the Web of Data. It describes the different kinds of data that exist, their topology, and their storing and indexing techniques. The second part is dedicated to Web Search. It presents different types of search, like the exploratory or the path-oriented, alongside methods for their efficient and effective implementation. Other related topics included in this part are the use of uncertainty in query answering, the exploitation of ontologies, and the use of semantics in mashup design and operation. The focus of the third part is on linked data, and more specifically, on applying ideas originating in recommender systems on linked data management, and on techniques for the efficiently querying answering on linked data.

Content

Inhalt: Introduction.- Part I Introduction to Web of Data.- Topology of the Web of Data.- Storing and Indexing Massive RDF Data Sets.- Designing Exploratory Search Applications upon Web Data Sources.- Part II Search over the Web.- Path-oriented Keyword Search query over RDF.- Interactive Query Construction for Keyword Search on the SemanticWeb.- Understanding the Semantics of Keyword Queries on Relational DataWithout Accessing the Instance.- Keyword-Based Search over Semantic Data.- Semantic Link Discovery over Relational Data.- Embracing Uncertainty in Entity Linking.- The Return of the Entity-Relationship Model: Ontological Query Answering.- Linked Data Services and Semantics-enabled Mashup.- Part III Linked Data Search engines.- A Recommender System for Linked Data.- Flint: from Web Pages to Probabilistic Semantic Data.- Searching and Browsing Linked Data with SWSE.

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Abstract

This book describes efficient and effective techniques for harnessing the power of Linked Data by tackling the various aspects of managing its growing volume: storing, querying, reasoning, provenance management and benchmarking. To this end, Chapter 1 introduces the main concepts of the Semantic Web and Linked Data and provides a roadmap for the book. Next, Chapter 2 briefly presents the basic concepts underpinning Linked Data technologies that are discussed in the book. Chapter 3 then offers an overview of various techniques and systems for centrally querying RDF datasets, and Chapter 4 outlines various techniques and systems for efficiently querying large RDF datasets in distributed environments. Subsequently, Chapter 5 explores how streaming requirements are addressed in current, state-of-the-art RDF stream data processing. Chapter 6 covers performance and scaling issues of distributed RDF reasoning systems, while Chapter 7 details benchmarks for RDF query engines and instance matching systems. Chapter 8 addresses the provenance management for Linked Data and presents the different provenance models developed. Lastly, Chapter 9 offers a brief summary, highlighting and providing insights into some of the open challenges and research directions. Providing an updated overview of methods, technologies and systems related to Linked Data this book is mainly intended for students and researchers who are interested in the Linked Data domain. It enables students to gain an understanding of the foundations and underpinning technologies and standards for Linked Data, while researchers benefit from the in-depth coverage of the emerging and ongoing advances in Linked Data storing, querying, reasoning, and provenance management systems. Further, it serves as a starting point to tackle the next research challenges in the domain of Linked Data management.