Search (196 results, page 10 of 10)

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Abstract

An increasing number of applications rely on RDF, OWL2, and SPARQL for storing and querying data. SPARQL, however, is not targeted towards end-users, and suitable query interfaces are needed. Faceted search is a prominent approach for end-user data access, and several RDF-based faceted search systems have been developed. There is, however, a lack of rigorous theoretical underpinning for faceted search in the context of RDF and OWL2. In this paper, we provide such solid foundations. We formalise faceted interfaces for this context, identify a fragment of first-order logic capturing the underlying queries, and study the complexity of answering such queries for RDF and OWL2 profiles. We then study interface generation and update, and devise efficiently implementable algorithms. Finally, we have implemented and tested our faceted search algorithms for scalability, with encouraging results.

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Abstract

Companies, governmental agencies and scientists produce a large amount of quantitative (research) data, consisting of measurements ranging from e.g. the surface temperatures of an ocean to the viscosity of a sample of mayonnaise. Such measurements are stored in tables in e.g. spreadsheet files and research reports. To integrate and reuse such data, it is necessary to have a semantic description of the data. However, the notation used is often ambiguous, making automatic interpretation and conversion to RDF or other suitable format diffiult. For example, the table header cell "f(Hz)" refers to frequency measured in Hertz, but the symbol "f" can also refer to the unit farad or the quantities force or luminous flux. Current annotation tools for this task either work on less ambiguous data or perform a more limited task. We introduce new disambiguation strategies based on an ontology, which allows to improve performance on "sloppy" datasets not yet targeted by existing systems.

Type

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Abstract

The number of publications in mathematics increases faster each year. Presently far more than 100,000 mathematically relevant journal articles and books are published annually. Efficient and high-quality content analysis of this material is important for mathematical bibliographic services such as ZBMath or MathSciNet. Content analysis has different facets and levels: classification, keywords, abstracts and reviews, and (in the future) formula analysis. It is the opinion of the authors that the different levels have to be enhanced and combined using the methods and technology of the Semantic Web. In the presentation, the problems and deficits of the existing methods and tools, the state of the art and current activities are discussed. As a first step, the Mathematical Subject Classification Scheme (MSC), has been encoded with Simple Knowledge Organization System (SKOS) and Resource Description Framework (RDF) at its recent revision to MSC2010. The use of SKOS principally opens new possibilities for the enrichment and wider deployment of this classification scheme and for machine-based content analysis of mathematical publications.

Source

Classification and ontology: formal approaches and access to knowledge: proceedings of the International UDC Seminar, 19-20 September 2011, The Hague, The Netherlands. Eds.: A. Slavic u. E. Civallero

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Abstract

In Linked Data, the use of owl:sameAs is ubiquitous in 'inter-linking' data-sets. However, there is a lurking suspicion within the Linked Data community that this use of owl:sameAs may be somehow incorrect, in particular with regards to its interactions with inference. In fact, owl:sameAs can be considered just one type of 'identity link', a link that declares two items to be identical in some fashion. After reviewing the definitions and history of the problem of identity in philosophy and knowledge representation, we outline four alternative readings of owl:sameAs, showing with examples how it is being (ab)used on the Web of data. Then we present possible solutions to this problem by introducing alternative identity links that rely on named graphs.

Type

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Abstract

Medical insurance fraud is common in many countries' medical insurance systems and represents a serious threat to the insurance funds and the benefits of patients. In this paper, we present an inference model of medical insurance fraud detection, based on a medical detection domain ontology that incorporates the knowledge base provided by the Medical Terminology, NKIMed, and Chinese Library Classification systems. Through analyzing the behaviors of irregular and fraudulent medical services, we defined the scope of the medical domain ontology relevant to the task and built the ontology about medical sciences and medical service behaviors. The ontology then utilizes Semantic Web Rule Language (SWRL) and Java Expert System Shell (JESS) to detect medical irregularities and mine implicit knowledge. The system can be used to improve the management of medical insurance risks.

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Abstract

We present Broccoli, a fast and easy-to-use search engine forwhat we call semantic full-text search. Semantic full-textsearch combines the capabilities of standard full-text searchand ontology search. The search operates on four kinds ofobjects: ordinary words (e.g., edible), classes (e.g., plants), instances (e.g.,Broccoli), and relations (e.g., occurs-with or native-to). Queries are trees, where nodes are arbitrary bags of these objects, and arcs are relations. The user interface guides the user in incrementally constructing such trees by instant (search-as-you-type) suggestions of words, classes, instances, or relations that lead to good hits. Both standard full-text search and pure ontology search are included as special cases. In this paper, we describe the query language of Broccoli, a new kind of index that enables fast processing of queries from that language as well as fast query suggestion, the natural language processing required, and the user interface. We evaluated query times and result quality on the full version of the English Wikipedia (32 GB XML dump) combined with the YAGO ontology (26 million facts). We have implemented a fully functional prototype based on our ideas, see: http://broccoli.informatik.uni-freiburg.de.

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Abstract

Ontology is the tool for representing knowledge in the fields of knowledge organization and artificial intelligence, and in the past decade, has gained attention in the semantic web as well. The main necessity in developing an ontology is generating a hierarchical structure of the concepts and the next requirement is creating and determining the type of the semantic relations among concepts. The present article introduces a semi-automated method for enriching semantic relations in the basic sciences ontology, which was developed based on domain-specific thesauri. In the proposed method, first the hierarchical relations in the ontology are reviewed and refined in order to distinguish their different types. In the next step, the concepts in the ontology are classified and the semantic relations among the concepts, based on the associative relationships in the thesaurus and semantic relation patterns extracted from a top-level ontology, are distinguished and added to the ontology. Using this method, semantic relations in the area of chemistry in the basic sciences ontology were refined and enriched. Almost seventy percent of the associative relationships were directly converted to semantic relations in the ontology. The remaining thirty percent are the inter-concept relations that can be concluded from other relations if the other associative relationships are correctly converted to semantic relations.

Type

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Abstract

Nowadays, eHealth and pHealth solutions have to meet advanced interoperability challenges. Enabling pervasive computing and even autonomic computing, pHealth system architectures cover many domains, scientifically managed by specialized disciplines using their specific ontologies. Therefore, semantic interoperability has to advance from a communication protocol to an ontology coordination challenge including semantic integration, bringing knowledge representation and artificial intelligence on the table. The resulting solutions comprehensively support multi-lingual and multi-jurisdictional environments.

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Abstract

The usefulness of online geological maps is hindered by linguistic barriers. Multilingual geoscience thesauri alleviate linguistic barriers of geological maps. However, the benefits of multilingual geoscience thesauri for online geological maps are less studied. In this regard, we developed a multilingual thesaurus of geological time scale (GTS) to alleviate linguistic barriers of GTS records among online geological maps. We extended the Simple Knowledge Organization System (SKOS) model to represent the ordinal hierarchical structure of GTS terms. We collected GTS terms in seven languages and encoded them into a thesaurus by using the extended SKOS model. We implemented methods of characteristic-oriented term retrieval in JavaScript programs for accessing Web Map Services (WMS), recognizing GTS terms, and making translations. With the developed thesaurus and programs, we set up a pilot system to test recognitions and translations of GTS terms in online geological maps. Results of this pilot system proved the accuracy of the developed thesaurus and the functionality of the developed programs. Therefore, with proper deployments, SKOS-based multilingual geoscience thesauri can be functional for alleviating linguistic barriers among online geological maps and, thus, improving their interoperability.

Type

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Abstract

Mathematics is a ubiquitous foundation of science, technology, and engineering. Specific areas, such as numeric and symbolic computation or logics, enjoy considerable software support. Working mathematicians have recently started to adopt Web 2.0 environment, such as blogs and wikis, but these systems lack machine support for knowledge organization and reuse, and they are disconnected from tools such as computer algebra systems or interactive proof assistants.We argue that such scenarios will benefit from Semantic Web technology. Conversely, mathematics is still underrepresented on the Web of [Linked] Data. There are mathematics-related Linked Data, for example statistical government data or scientific publication databases, but their mathematical semantics has not yet been modeled. We argue that the services for the Web of Data will benefit from a deeper representation of mathematical knowledge. Mathematical knowledge comprises logical and functional structures - formulæ, statements, and theories -, a mixture of rigorous natural language and symbolic notation in documents, application-specific metadata, and discussions about conceptualizations, formalizations, proofs, and (counter-)examples. Our review of approaches to representing these structures covers ontologies for mathematical problems, proofs, interlinked scientific publications, scientific discourse, as well as mathematical metadata vocabularies and domain knowledge from pure and applied mathematics. Many fields of mathematics have not yet been implemented as proper Semantic Web ontologies; however, we show that MathML and OpenMath, the standard XML-based exchange languages for mathematical knowledge, can be fully integrated with RDF representations in order to contribute existing mathematical knowledge to theWeb of Data. We conclude with a roadmap for getting the mathematical Web of Data started: what datasets to publish, how to interlink them, and how to take advantage of these new connections.

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Content

Programm mit Links auf die Präsentationen: Armando Stellato, Ahsan Morshed, Gudrun Johannsen, Yves Jacques, Caterina Caracciolo, Sachit Rajbhandari, Imma Subirats, Johannes Keizer: A Collaborative Framework for Managing and Publishing KOS - Christian Mader, Bernhard Haslhofer: Quality Criteria for Controlled Web Vocabularies - Ahsan Morshed, Benjamin Zapilko, Gudrun Johannsen, Philipp Mayr, Johannes Keizer: Evaluating approaches to automatically match thesauri from different domains for Linked Open Data - Johan De Smedt: SKOS extensions to cover mapping requirements - Mark Tomko: Translating biological data sets Into Linked Data - Daniel Kless: Ontologies and thesauri - similarities and differences - Antoine Isaac, Jacco van Ossenbruggen: Europeana and semantic alignment of vocabularies - Douglas Tudhope: Complementary use of ontologies and (other) KOS - Wilko van Hoek, Brigitte Mathiak, Philipp Mayr, Sascha Schüller: Comparing the accuracy of the semantic similarity provided by the Normalized Google Distance (NGD) and the Search Term Recommender (STR) - Denise Bedford: Selecting and Weighting Semantically Discovered Concepts as Social Tags - Stella Dextre Clarke, Johan De Smedt. ISO 25964-1: a new standard for development of thesauri and exchange of thesaurus data

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Abstract

In Linked Data, the use of owl:sameAs is ubiquitous in interlinking data-sets. There is however, ongoing discussion about its use, and potential misuse, particularly with regards to interactions with inference. In fact, owl:sameAs can be viewed as encoding only one point on a scale of similarity, one that is often too strong for many of its current uses. We describe how referentially opaque contexts that do not allow inference exist, and then outline some varieties of referentially-opaque alternatives to owl:sameAs. Finally, we report on an empirical experiment over randomly selected owl:sameAs statements from the Web of data. This theoretical apparatus and experiment shed light upon how owl:sameAs is being used (and misused) on the Web of data.

Type

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Abstract

The power of search is with no doubt one of the main aspects for the success of the Web. Currently available search engines on the Web allow to return results with a high precision. Nevertheless, if we limit our attention only to lookup search we are missing another important search task. In exploratory search, the user is willing not only to find documents relevant with respect to her query but she is also interested in learning, discovering and understanding novel knowledge on complex and sometimes unknown topics. In the paper we address this issue presenting LED, a web based system that aims to improve (lookup) Web search by enabling users to properly explore knowledge associated to her query. We rely on DBpedia to explore the semantics of keywords within the query thus suggesting potentially interesting related topics/keywords to the user.

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Abstract

The two-volume set LNCS 6496 and 6497 constitutes the refereed proceedings of the 9th International Semantic Web Conference, ISWC 2010, held in Shanghai, China, during November 7-11, 2010. Part I contains 51 papers out of 578 submissions to the research track. Part II contains 18 papers out of 66 submissions to the semantic Web in-use track, 6 papers out of 26 submissions to the doctoral consortium track, and also 4 invited talks. Each submitted paper were carefully reviewed. The International Semantic Web Conferences (ISWC) constitute the major international venue where the latest research results and technical innovations on all aspects of the Semantic Web are presented. ISWC brings together researchers, practitioners, and users from the areas of artificial intelligence, databases, social networks, distributed computing, Web engineering, information systems, natural language processing, soft computing, and human computer interaction to discuss the major challenges and proposed solutions, the success stories and failures, as well the visions that can advance research and drive innovation in the Semantic Web.

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Abstract

The two-volume set LNCS 6496 and 6497 constitutes the refereed proceedings of the 9th International Semantic Web Conference, ISWC 2010, held in Shanghai, China, during November 7-11, 2010. Part I contains 51 papers out of 578 submissions to the research track. Part II contains 18 papers out of 66 submissions to the semantic Web in-use track, 6 papers out of 26 submissions to the doctoral consortium track, and also 4 invited talks. Each submitted paper were carefully reviewed. The International Semantic Web Conferences (ISWC) constitute the major international venue where the latest research results and technical innovations on all aspects of the Semantic Web are presented. ISWC brings together researchers, practitioners, and users from the areas of artificial intelligence, databases, social networks, distributed computing, Web engineering, information systems, natural language processing, soft computing, and human computer interaction to discuss the major challenges and proposed solutions, the success stories and failures, as well the visions that can advance research and drive innovation in the Semantic Web.