Search (127 results, page 1 of 7)

  • × theme_ss:"Semantic Web"
  • × year_i:[2010 TO 2020}
  1. Hollink, L.; Assem, M. van: Estimating the relevance of search results in the Culture-Web : a study of semantic distance measures (2010) 0.04 
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    Abstract
    More and more cultural heritage institutions publish their collections, vocabularies and metadata on the Web. The resulting Web of linked cultural data opens up exciting new possibilities for searching and browsing through these cultural heritage collections. We report on ongoing work in which we investigate the estimation of relevance in this Web of Culture. We study existing measures of semantic distance and how they apply to two use cases. The use cases relate to the structured, multilingual and multimodal nature of the Culture Web. We distinguish between measures using the Web, such as Google distance and PMI, and measures using the Linked Data Web, i.e. the semantic structure of metadata vocabularies. We perform a small study in which we compare these semantic distance measures to human judgements of relevance. Although it is too early to draw any definitive conclusions, the study provides new insights into the applicability of semantic distance measures to the Web of Culture, and clear starting points for further research.
    Date
    26.12.2011 13:40:22
  2. Brunetti, J.M.; Roberto García, R.: User-centered design and evaluation of overview components for semantic data exploration (2014) 0.04 
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    Abstract
    Purpose - The growing volumes of semantic data available in the web result in the need for handling the information overload phenomenon. The potential of this amount of data is enormous but in most cases it is very difficult for users to visualize, explore and use this data, especially for lay-users without experience with Semantic Web technologies. The paper aims to discuss these issues. Design/methodology/approach - The Visual Information-Seeking Mantra "Overview first, zoom and filter, then details-on-demand" proposed by Shneiderman describes how data should be presented in different stages to achieve an effective exploration. The overview is the first user task when dealing with a data set. The objective is that the user is capable of getting an idea about the overall structure of the data set. Different information architecture (IA) components supporting the overview tasks have been developed, so they are automatically generated from semantic data, and evaluated with end-users. Findings - The chosen IA components are well known to web users, as they are present in most web pages: navigation bars, site maps and site indexes. The authors complement them with Treemaps, a visualization technique for displaying hierarchical data. These components have been developed following an iterative User-Centered Design methodology. Evaluations with end-users have shown that they get easily used to them despite the fact that they are generated automatically from structured data, without requiring knowledge about the underlying semantic technologies, and that the different overview components complement each other as they focus on different information search needs. Originality/value - Obtaining semantic data sets overviews cannot be easily done with the current semantic web browsers. Overviews become difficult to achieve with large heterogeneous data sets, which is typical in the Semantic Web, because traditional IA techniques do not easily scale to large data sets. There is little or no support to obtain overview information quickly and easily at the beginning of the exploration of a new data set. This can be a serious limitation when exploring a data set for the first time, especially for lay-users. The proposal is to reuse and adapt existing IA components to provide this overview to users and show that they can be generated automatically from the thesaurus and ontologies that structure semantic data while providing a comparable user experience to traditional web sites.
    Date
    20. 1.2015 18:30:22
    Source
    Aslib journal of information management. 66(2014) no.5, S.519-536
    Theme
    Semantisches Umfeld in Indexierung u. Retrieval
  3. Smith, D.A.; Shadbolt, N.R.: FacetOntology : expressive descriptions of facets in the Semantic Web (2012) 0.04 
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    Abstract
    The formal structure of the information on the Semantic Web lends itself to faceted browsing, an information retrieval method where users can filter results based on the values of properties ("facets"). Numerous faceted browsers have been created to browse RDF and Linked Data, but these systems use their own ontologies for defining how data is queried to populate their facets. Since the source data is the same format across these systems (specifically, RDF), we can unify the different methods of describing how to quer the underlying data, to enable compatibility across systems, and provide an extensible base ontology for future systems. To this end, we present FacetOntology, an ontology that defines how to query data to form a faceted browser, and a number of transformations and filters that can be applied to data before it is shown to users. FacetOntology overcomes limitations in the expressivity of existing work, by enabling the full expressivity of SPARQL when selecting data for facets. By applying a FacetOntology definition to data, a set of facets are specified, each with queries and filters to source RDF data, which enables faceted browsing systems to be created using that RDF data.
    Theme
    Semantisches Umfeld in Indexierung u. Retrieval
  4. Semantic search over the Web (2012) 0.04 
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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.
    Theme
    Semantisches Umfeld in Indexierung u. Retrieval
  5. Semantic applications (2018) 0.04 
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    Abstract
    This book describes proven methodologies for developing semantic applications: software applications which explicitly or implicitly uses the semantics (i.e., the meaning) of a domain terminology in order to improve usability, correctness, and completeness. An example is semantic search, where synonyms and related terms are used for enriching the results of a simple text-based search. Ontologies, thesauri or controlled vocabularies are the centerpiece of semantic applications. The book includes technological and architectural best practices for corporate use.
    Content
    Introduction.- Ontology Development.- Compliance using Metadata.- Variety Management for Big Data.- Text Mining in Economics.- Generation of Natural Language Texts.- Sentiment Analysis.- Building Concise Text Corpora from Web Contents.- Ontology-Based Modelling of Web Content.- Personalized Clinical Decision Support for Cancer Care.- Applications of Temporal Conceptual Semantic Systems.- Context-Aware Documentation in the Smart Factory.- Knowledge-Based Production Planning for Industry 4.0.- Information Exchange in Jurisdiction.- Supporting Automated License Clearing.- Managing cultural assets: Implementing typical cultural heritage archive's usage scenarios via Semantic Web technologies.- Semantic Applications for Process Management.- Domain-Specific Semantic Search Applications.
    LCSH
    Information storage and retrieval
    Management of Computing and Information Systems
    Information Storage and Retrieval
    RSWK
    Information Retrieval
    Series
    methodology, technology, corporate use
    Subject
    Information Retrieval
    Information storage and retrieval
    Management of Computing and Information Systems
    Information Storage and Retrieval
  6. Bergamaschi, S.; Domnori, E.; Guerra, F.; Rota, S.; Lado, R.T.; Velegrakis, Y.: Understanding the semantics of keyword queries on relational data without accessing the instance (2012) 0.04 
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    Abstract
    The birth of the Web has brought an exponential growth to the amount of the information that is freely available to the Internet population, overloading users and entangling their efforts to satisfy their information needs. Web search engines such Google, Yahoo, or Bing have become popular mainly due to the fact that they offer an easy-to-use query interface (i.e., based on keywords) and an effective and efficient query execution mechanism. The majority of these search engines do not consider information stored on the deep or hidden Web [9,28], despite the fact that the size of the deep Web is estimated to be much bigger than the surface Web [9,47]. There have been a number of systems that record interactions with the deep Web sources or automatically submit queries them (mainly through their Web form interfaces) in order to index their context. Unfortunately, this technique is only partially indexing the data instance. Moreover, it is not possible to take advantage of the query capabilities of data sources, for example, of the relational query features, because their interface is often restricted from the Web form. Besides, Web search engines focus on retrieving documents and not on querying structured sources, so they are unable to access information based on concepts.
    Theme
    Semantisches Umfeld in Indexierung u. Retrieval
  7. Fernández, M.; Cantador, I.; López, V.; Vallet, D.; Castells, P.; Motta, E.: Semantically enhanced Information Retrieval : an ontology-based approach (2011) 0.04 
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    Abstract
    Currently, techniques for content description and query processing in Information Retrieval (IR) are based on keywords, and therefore provide limited capabilities to capture the conceptualizations associated with user needs and contents. Aiming to solve the limitations of keyword-based models, the idea of conceptual search, understood as searching by meanings rather than literal strings, has been the focus of a wide body of research in the IR field. More recently, it has been used as a prototypical scenario (or even envisioned as a potential "killer app") in the Semantic Web (SW) vision, since its emergence in the late nineties. However, current approaches to semantic search developed in the SW area have not yet taken full advantage of the acquired knowledge, accumulated experience, and technological sophistication achieved through several decades of work in the IR field. Starting from this position, this work investigates the definition of an ontology-based IR model, oriented to the exploitation of domain Knowledge Bases to support semantic search capabilities in large document repositories, stressing on the one hand the use of fully fledged ontologies in the semantic-based perspective, and on the other hand the consideration of unstructured content as the target search space. The major contribution of this work is an innovative, comprehensive semantic search model, which extends the classic IR model, addresses the challenges of the massive and heterogeneous Web environment, and integrates the benefits of both keyword and semantic-based search. Additional contributions include: an innovative rank fusion technique that minimizes the undesired effects of knowledge sparseness on the yet juvenile SW, and the creation of a large-scale evaluation benchmark, based on TREC IR evaluation standards, which allows a rigorous comparison between IR and SW approaches. Conducted experiments show that our semantic search model obtained comparable and better performance results (in terms of MAP and P@10 values) than the best TREC automatic system.
    Series
    JWS special issue on Semantic Search
    Source
    Web semantics: science, services and agents on the World Wide Web. 9(2011) no.4, S.434-452
  8. Kara, S.: ¬An ontology-based retrieval system using semantic indexing (2012) 0.04 
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    Abstract
    In this thesis, we present an ontology-based information extraction and retrieval system and its application to soccer domain. In general, we deal with three issues in semantic search, namely, usability, scalability and retrieval performance. We propose a keyword-based semantic retrieval approach. The performance of the system is improved considerably using domain-specific information extraction, inference and rules. Scalability is achieved by adapting a semantic indexing approach. The system is implemented using the state-of-the-art technologies in SemanticWeb and its performance is evaluated against traditional systems as well as the query expansion methods. Furthermore, a detailed evaluation is provided to observe the performance gain due to domain-specific information extraction and inference. Finally, we show how we use semantic indexing to solve simple structural ambiguities.
    Content
    Thesis submitted to the Graduate School of Natural and Applied Sciences of Middle East Technical University in partial fulfilment of the requirements for the degree of Master of science in Computer Engineering (XII, 57 S.)
  9. Vocht, L. De: Exploring semantic relationships in the Web of Data : Semantische relaties verkennen in data op het web (2017) 0.03 
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    Abstract
    After the launch of the World Wide Web, it became clear that searching documentson the Web would not be trivial. Well-known engines to search the web, like Google, focus on search in web documents using keywords. The documents are structured and indexed to ensure keywords match documents as accurately as possible. However, searching by keywords does not always suice. It is oen the case that users do not know exactly how to formulate the search query or which keywords guarantee retrieving the most relevant documents. Besides that, it occurs that users rather want to browse information than looking up something specific. It turned out that there is need for systems that enable more interactivity and facilitate the gradual refinement of search queries to explore the Web. Users expect more from the Web because the short keyword-based queries they pose during search, do not suffice for all cases. On top of that, the Web is changing structurally. The Web comprises, apart from a collection of documents, more and more linked data, pieces of information structured so they can be processed by machines. The consequently applied semantics allow users to exactly indicate machines their search intentions. This is made possible by describing data following controlled vocabularies, concept lists composed by experts, published uniquely identifiable on the Web. Even so, it is still not trivial to explore data on the Web. There is a large variety of vocabularies and various data sources use different terms to identify the same concepts.
    This PhD-thesis describes how to effectively explore linked data on the Web. The main focus is on scenarios where users want to discover relationships between resources rather than finding out more about something specific. Searching for a specific document or piece of information fits in the theoretical framework of information retrieval and is associated with exploratory search. Exploratory search goes beyond 'looking up something' when users are seeking more detailed understanding, further investigation or navigation of the initial search results. The ideas behind exploratory search and querying linked data merge when it comes to the way knowledge is represented and indexed by machines - how data is structured and stored for optimal searchability. Queries and information should be aligned to facilitate that searches also reveal connections between results. This implies that they take into account the same semantic entities, relevant at that moment. To realize this, we research three techniques that are evaluated one by one in an experimental set-up to assess how well they succeed in their goals. In the end, the techniques are applied to a practical use case that focuses on forming a bridge between the Web and the use of digital libraries in scientific research. Our first technique focuses on the interactive visualization of search results. Linked data resources can be brought in relation with each other at will. This leads to complex and diverse graphs structures. Our technique facilitates navigation and supports a workflow starting from a broad overview on the data and allows narrowing down until the desired level of detail to then broaden again. To validate the flow, two visualizations where implemented and presented to test-users. The users judged the usability of the visualizations, how the visualizations fit in the workflow and to which degree their features seemed useful for the exploration of linked data.
    The ideas behind exploratory search and querying linked data merge when it comes to the way knowledge is represented and indexed by machines - how data is structured and stored for optimal searchability. eries and information should be aligned to facilitate that searches also reveal connections between results. This implies that they take into account the same semantic entities, relevant at that moment. To realize this, we research three techniques that are evaluated one by one in an experimental set-up to assess how well they succeed in their goals. In the end, the techniques are applied to a practical use case that focuses on forming a bridge between the Web and the use of digital libraries in scientific research.
    Our first technique focuses on the interactive visualization of search results. Linked data resources can be brought in relation with each other at will. This leads to complex and diverse graphs structures. Our technique facilitates navigation and supports a workflow starting from a broad overview on the data and allows narrowing down until the desired level of detail to then broaden again. To validate the flow, two visualizations where implemented and presented to test-users. The users judged the usability of the visualizations, how the visualizations fit in the workflow and to which degree their features seemed useful for the exploration of linked data. There is a difference in the way users interact with resources, visually or textually, and how resources are represented for machines to be processed by algorithms. This difference complicates bridging the users' intents and machine executable queries. It is important to implement this 'translation' mechanism to impact the search as favorable as possible in terms of performance, complexity and accuracy. To do this, we explain a second technique, that supports such a bridging component. Our second technique is developed around three features that support the search process: looking up, relating and ranking resources. The main goal is to ensure that resources in the results are as precise and relevant as possible. During the evaluation of this technique, we did not only look at the precision of the search results but also investigated how the effectiveness of the search evolved while the user executed certain actions sequentially.
    When we speak about finding relationships between resources, it is necessary to dive deeper in the structure. The graph structure of linked data where the semantics give meaning to the relationships between resources enable the execution of pathfinding algorithms. The assigned weights and heuristics are base components of such algorithms and ultimately define (the order) which resources are included in a path. These paths explain indirect connections between resources. Our third technique proposes an algorithm that optimizes the choice of resources in terms of serendipity. Some optimizations guard the consistence of candidate-paths where the coherence of consecutive connections is maximized to avoid trivial and too arbitrary paths. The implementation uses the A* algorithm, the de-facto reference when it comes to heuristically optimized minimal cost paths. The effectiveness of paths was measured based on common automatic metrics and surveys where the users could indicate their preference for paths, generated each time in a different way. Finally, all our techniques are applied to a use case about publications in digital libraries where they are aligned with information about scientific conferences and researchers. The application to this use case is a practical example because the different aspects of exploratory search come together. In fact, the techniques also evolved from the experiences when implementing the use case. Practical details about the semantic model are explained and the implementation of the search system is clarified module by module. The evaluation positions the result, a prototype of a tool to explore scientific publications, researchers and conferences next to some important alternatives.
  10. Hogan, A.; Harth, A.; Umbrich, J.; Kinsella, S.; Polleres, A.; Decker, S.: Searching and browsing Linked Data with SWSE : the Semantic Web Search Engine (2011) 0.03 
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    Abstract
    In this paper, we discuss the architecture and implementation of the Semantic Web Search Engine (SWSE). Following traditional search engine architecture, SWSE consists of crawling, data enhancing, indexing and a user interface for search, browsing and retrieval of information; unlike traditional search engines, SWSE operates over RDF Web data - loosely also known as Linked Data - which implies unique challenges for the system design, architecture, algorithms, implementation and user interface. In particular, many challenges exist in adopting Semantic Web technologies for Web data: the unique challenges of the Web - in terms of scale, unreliability, inconsistency and noise - are largely overlooked by the current Semantic Web standards. Herein, we describe the current SWSE system, initially detailing the architecture and later elaborating upon the function, design, implementation and performance of each individual component. In so doing, we also give an insight into how current Semantic Web standards can be tailored, in a best-effort manner, for use on Web data. Throughout, we offer evaluation and complementary argumentation to support our design choices, and also offer discussion on future directions and open research questions. Later, we also provide candid discussion relating to the difficulties currently faced in bringing such a search engine into the mainstream, and lessons learnt from roughly six years working on the Semantic Web Search Engine project.
  11. ¬The Semantic Web: latest advances and new domains : 12th European Semantic Web Conference, ESWC 2015 Portoroz, Slovenia, May 31 -- June 4, 2015. Proceedings (2015) 0.03 
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    Abstract
    This book constitutes the refereed proceedings of the 12th Extended Semantic Web Conference, ESWC 2014, held in Anissaras, Portoroz, Slovenia, in May/June 2015. The 43 revised full papers presented together with three invited talks were carefully reviewed and selected from 164 submissions. This program was completed by a demonstration and poster session, in which researchers had the chance to present their latest results and advances in the form of live demos. In addition, the PhD Symposium program included 12 contributions, selected out of 16 submissions. The core tracks of the research conference were complemented with new tracks focusing on linking machine and human computation at web scale (cognition and Semantic Web, Human Computation and Crowdsourcing) beside the following subjects Vocabularies, Schemas, Ontologies, Reasoning, Linked Data, Semantic Web and Web Science, Semantic Data Management, Big data, Scalability, Natural Language Processing and Information Retrieval, Machine Learning, Mobile Web, Internet of Things and Semantic Streams, Services, Web APIs and the Web of Things, Cognition and Semantic Web, Human Computation and Crowdsourcing and In-Use Industrial Track as well
    Content
    Inhalt (Auszug) Vocabularies, Schemas, Ontologies: Requirements for and Evaluation of User Support for Large-Scale Ontology Alignment / Valentina Ivanova, Patrick Lambrix, and Johan Åberg -- RODI: A Benchmark for Automatic Mapping Generation in Relational-to-Ontology Data Integration / Christoph Pinkel, Carsten Binnig, Ernesto Jiménez-Ruiz, Wolfgang May, Dominique Ritze, Martin G. Skjæveland, Alessandro Solimando, and Evgeny Kharlamov -- VocBench: A Web Application for Collaborative Development of Multilingual Thesauri. / Armando Stellato, Sachit Rajbhandari, Andrea Turbati, Manuel Fiorelli, Caterina Caracciolo, Tiziano Lorenzetti, Johannes Keizer, and Maria Teresa Pazienza -- Leveraging and Balancing Heterogeneous Sources of Evidence in Ontology Learning / Gerhard Wohlgenannt Natural Language Processing and Information Retrieval Learning a Cross-Lingual Semantic Representation of Relations Expressed in Text / Achim Rettinger, Artem Schumilin, Steffen Thoma, and Basil Ell
  12. Manaf, N.A. Abdul; Bechhofer, S.; Stevens, R.: ¬The current state of SKOS vocabularies on the Web (2012) 0.03 
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    Abstract
    We present a survey of the current state of Simple Knowledge Organization System (SKOS) vocabularies on the Web. Candidate vocabularies were gathered through collections and web crawling, with 478 identified as complying to a given definition of a SKOS vocabulary. Analyses were then conducted that included investigation of the use of SKOS constructs; the use of SKOS semantic relations and lexical labels; and the structure of vocabularies in terms of the hierarchical and associative relations, branching factors and the depth of the vocabularies. Even though SKOS concepts are considered to be the core of SKOS vocabularies, our findings were that not all SKOS vocabularies published explicitly declared SKOS concepts in the vocabularies. Almost one-third of th SKOS vocabularies collected fall into the category of term lists, with no use of any SKOS semantic relations. As concept labelling is core to SKOS vocabularies, a surprising find is that not all SKOS vocabularies use SKOS lexical labels, whether skos:prefLabel or skos:altLabel, for their concepts. The branching factors and maximum depth of the vocabularies have no direct relationship to the size of the vocabularies. We also observed some common modelling slips found in SKOS vocabularies. The survey is useful when considering, for example, converting artefacts such as OWL ontologies into SKOS, where a definition of typicality of SKOS vocabularies could be used to guide the conversion. Moreover, the survey results can serve to provide a better understanding of the modelling styles of the SKOS vocabularies published on the Web, especially when considering the creation of applications that utilize these vocabularies.
  13. Zhitomirsky-Geffet, M.; Bar-Ilan, J.: Towards maximal unification of semantically diverse ontologies for controversial domains (2014) 0.03 
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    Abstract
    Purpose - Ontologies are prone to wide semantic variability due to subjective points of view of their composers. The purpose of this paper is to propose a new approach for maximal unification of diverse ontologies for controversial domains by their relations. Design/methodology/approach - Effective matching or unification of multiple ontologies for a specific domain is crucial for the success of many semantic web applications, such as semantic information retrieval and organization, document tagging, summarization and search. To this end, numerous automatic and semi-automatic techniques were proposed in the past decade that attempt to identify similar entities, mostly classes, in diverse ontologies for similar domains. Apparently, matching individual entities cannot result in full integration of ontologies' semantics without matching their inter-relations with all other-related classes (and instances). However, semantic matching of ontological relations still constitutes a major research challenge. Therefore, in this paper the authors propose a new paradigm for assessment of maximal possible matching and unification of ontological relations. To this end, several unification rules for ontological relations were devised based on ontological reference rules, and lexical and textual entailment. These rules were semi-automatically implemented to extend a given ontology with semantically matching relations from another ontology for a similar domain. Then, the ontologies were unified through these similar pairs of relations. The authors observe that these rules can be also facilitated to reveal the contradictory relations in different ontologies. Findings - To assess the feasibility of the approach two experiments were conducted with different sets of multiple personal ontologies on controversial domains constructed by trained subjects. The results for about 50 distinct ontology pairs demonstrate a good potential of the methodology for increasing inter-ontology agreement. Furthermore, the authors show that the presented methodology can lead to a complete unification of multiple semantically heterogeneous ontologies. Research limitations/implications - This is a conceptual study that presents a new approach for semantic unification of ontologies by a devised set of rules along with the initial experimental evidence of its feasibility and effectiveness. However, this methodology has to be fully automatically implemented and tested on a larger dataset in future research. Practical implications - This result has implication for semantic search, since a richer ontology, comprised of multiple aspects and viewpoints of the domain of knowledge, enhances discoverability and improves search results. Originality/value - To the best of the knowledge, this is the first study to examine and assess the maximal level of semantic relation-based ontology unification.
    Date
    20. 1.2015 18:30:22
    Source
    Aslib journal of information management. 66(2014) no.5, S.494-518
  14. Sakr, S.; Wylot, M.; Mutharaju, R.; Le-Phuoc, D.; Fundulaki, I.: Linked data : storing, querying, and reasoning (2018) 0.03 
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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.
    LCSH
    Computers
    Information storage and retrieval
    Subject
    Computers
    Information storage and retrieval
  15. Metadata and semantics research : 7th Research Conference, MTSR 2013 Thessaloniki, Greece, November 19-22, 2013. Proceedings (2013) 0.03 
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    Abstract
    Metadata and semantics are integral to any information system and significant to the sphere of Web data. Research focusing on metadata and semantics is crucial for advancing our understanding and knowledge of metadata; and, more profoundly for being able to effectively discover, use, archive, and repurpose information. In response to this need, researchers are actively examining methods for generating, reusing, and interchanging metadata. Integrated with these developments is research on the application of computational methods, linked data, and data analytics. A growing body of work also targets conceptual and theoretical designs providing foundational frameworks for metadata and semantic applications. There is no doubt that metadata weaves its way into nearly every aspect of our information ecosystem, and there is great motivation for advancing the current state of metadata and semantics. To this end, it is vital that scholars and practitioners convene and share their work.
    The MTSR 2013 program and the contents of these proceedings show a rich diversity of research and practices, drawing on problems from metadata and semantically focused tools and technologies, linked data, cross-language semantics, ontologies, metadata models, and semantic system and metadata standards. The general session of the conference included 18 papers covering a broad spectrum of topics, proving the interdisciplinary field of metadata, and was divided into three main themes: platforms for research data sets, system architecture and data management; metadata and ontology validation, evaluation, mapping and interoperability; and content management. Metadata as a research topic is maturing, and the conference also supported the following five tracks: Metadata and Semantics for Open Repositories, Research Information Systems and Data Infrastructures; Metadata and Semantics for Cultural Collections and Applications; Metadata and Semantics for Agriculture, Food and Environment; Big Data and Digital Libraries in Health, Science and Technology; and European and National Projects, and Project Networking. Each track had a rich selection of papers, giving broader diversity to MTSR, and enabling deeper exploration of significant topics.
    All the papers underwent a thorough and rigorous peer-review process. The review and selection this year was highly competitive and only papers containing significant research results, innovative methods, or novel and best practices were accepted for publication. Only 29 of 89 submissions were accepted as full papers, representing 32.5% of the total number of submissions. Additional contributions covering noteworthy and important results in special tracks or project reports were accepted, totaling 42 accepted contributions. This year's conference included two outstanding keynote speakers. Dr. Stefan Gradmann, a professor arts department of KU Leuven (Belgium) and director of university library, addressed semantic research drawing from his work with Europeana. The title of his presentation was, "Towards a Semantic Research Library: Digital Humanities Research, Europeana and the Linked Data Paradigm". Dr. Michail Salampasis, associate professor from our conference host institution, the Department of Informatics of the Alexander TEI of Thessaloniki, presented new potential, intersecting search and linked data. The title of his talk was, "Rethinking the Search Experience: What Could Professional Search Systems Do Better?"
    Date
    17.12.2013 12:51:22
  16. Brambilla, M.; Ceri, S.: Designing exploratory search applications upon Web data sources (2012) 0.03 
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    Abstract
    Search is the preferred method to access information in today's computing systems. The Web, accessed through search engines, is universally recognized as the source for answering users' information needs. However, offering a link to a Web page does not cover all information needs. Even simple problems, such as "Which theater offers an at least three-stars action movie in London close to a good Italian restaurant," can only be solved by searching the Web multiple times, e.g., by extracting a list of the recent action movies filtered by ranking, then looking for movie theaters, then looking for Italian restaurants close to them. While search engines hint to useful information, the user's brain is the fundamental platform for information integration. An important trend is the availability of new, specialized data sources-the so-called "long tail" of the Web of data. Such carefully collected and curated data sources can be much more valuable than information currently available in Web pages; however, many sources remain hidden or insulated, in the lack of software solutions for bringing them to surface and making them usable in the search context. A new class of tailor-made systems, designed to satisfy the needs of users with specific aims, will support the publishing and integration of data sources for vertical domains; the user will be able to select sources based on individual or collective trust, and systems will be able to route queries to such sources and to provide easyto-use interfaces for combining them within search strategies, at the same time, rewarding the data source owners for each contribution to effective search. Efforts such as Google's Fusion Tables show that the technology for bringing hidden data sources to surface is feasible.
    Theme
    Semantisches Umfeld in Indexierung u. Retrieval
  17. Metadata and semantics research : 9th Research Conference, MTSR 2015, Manchester, UK, September 9-11, 2015, Proceedings (2015) 0.02 
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    Abstract
    This book constitutes the refereed proceedings of the 9th Metadata and Semantics Research Conference, MTSR 2015, held in Manchester, UK, in September 2015. The 35 full papers and 3 short papers presented together with 2 poster papers were carefully reviewed and selected from 76 submissions.
    Content
    The papers are organized in several sessions and tracks: general track on ontology evolution, engineering, and frameworks, semantic Web and metadata extraction, modelling, interoperability and exploratory search, data analysis, reuse and visualization; track on digital libraries, information retrieval, linked and social data; track on metadata and semantics for open repositories, research information systems and data infrastructure; track on metadata and semantics for agriculture, food and environment; track on metadata and semantics for cultural collections and applications; track on European and national projects.
    LCSH
    Information storage and retrieval systems
    Subject
    Information storage and retrieval systems
  18. Hooland, S. van; Verborgh, R.; Wilde, M. De; Hercher, J.; Mannens, E.; Wa, R.Van de: Evaluating the success of vocabulary reconciliation for cultural heritage collections (2013) 0.02 
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    Abstract
    The concept of Linked Data has made its entrance in the cultural heritage sector due to its potential use for the integration of heterogeneous collections and deriving additional value out of existing metadata. However, practitioners and researchers alike need a better understanding of what outcome they can reasonably expect of the reconciliation process between their local metadata and established controlled vocabularies which are already a part of the Linked Data cloud. This paper offers an in-depth analysis of how a locally developed vocabulary can be successfully reconciled with the Library of Congress Subject Headings (LCSH) and the Arts and Architecture Thesaurus (AAT) through the help of a general-purpose tool for interactive data transformation (OpenRefine). Issues negatively affecting the reconciliation process are identified and solutions are proposed in order to derive maximum value from existing metadata and controlled vocabularies in an automated manner.
    Date
    22. 3.2013 19:29:20
    Source
    Journal of the American Society for Information Science and Technology. 64(2013) no.3, S.464-479
  19. Oliveira Machado, L.M.; Souza, R.R.; Simões, M. da Graça: Semantic web or web of data? : a diachronic study (1999 to 2017) of the publications of Tim Berners-Lee and the World Wide Web Consortium (2019) 0.02 
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    Abstract
    The web has been, in the last decades, the place where information retrieval achieved its maximum importance, given its ubiquity and the sheer volume of information. However, its exponential growth made the retrieval task increasingly hard, relying in its effectiveness on idiosyncratic and somewhat biased ranking algorithms. To deal with this problem, a "new" web, called the Semantic Web (SW), was proposed, bringing along concepts like "Web of Data" and "Linked Data," although the definitions and connections among these concepts are often unclear. Based on a qualitative approach built over a literature review, a definition of SW is presented, discussing the related concepts sometimes used as synonyms. It concludes that the SW is a comprehensive and ambitious construct that includes the great purpose of making the web a global database. It also follows the specifications developed and/or associated with its operationalization and the necessary procedures for the connection of data in an open format on the web. The goals of this comprehensive SW are the union of two outcomes still tenuously connected: the virtually unlimited possibility of connections between data-the web domain-with the potentiality of the automated inference of "intelligent" systems-the semantic component.
    Source
    Journal of the Association for Information Science and Technology. 70(2019) no.7, S.701-714
  20. Narock, T.; Zhou, L.; Yoon, V.: Semantic similarity of ontology instances using polarity mining (2013) 0.02 
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    Abstract
    Semantic similarity is vital to many areas, such as information retrieval. Various methods have been proposed with a focus on comparing unstructured text documents. Several of these have been enhanced with ontology; however, they have not been applied to ontology instances. With the growth in ontology instance data published online through, for example, Linked Open Data, there is an increasing need to apply semantic similarity to ontology instances. Drawing on ontology-supported polarity mining (OSPM), we propose an algorithm that enhances the computation of semantic similarity with polarity mining techniques. The algorithm is evaluated with online customer review data. The experimental results show that the proposed algorithm outperforms the baseline algorithm in multiple settings.
    Source
    Journal of the American Society for Information Science and Technology. 64(2013) no.2, S.416-427
    Theme
    Semantisches Umfeld in Indexierung u. Retrieval

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