Search (56 results, page 1 of 3)

0.0991658 = product of:
  0.1983316 = sum of:
    0.0495829 = product of:
      0.1487487 = sum of:
        0.1487487 = weight(_text_:3a in 701) [ClassicSimilarity], result of:
          0.1487487 = score(doc=701,freq=2.0), product of:
            0.39700332 = queryWeight, product of:
              8.478011 = idf(docFreq=24, maxDocs=44218)
              0.046827413 = queryNorm
            0.3746787 = fieldWeight in 701, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              8.478011 = idf(docFreq=24, maxDocs=44218)
              0.03125 = fieldNorm(doc=701)
      0.33333334 = coord(1/3)
    0.1487487 = weight(_text_:2f in 701) [ClassicSimilarity], result of:
      0.1487487 = score(doc=701,freq=2.0), product of:
        0.39700332 = queryWeight, product of:
          8.478011 = idf(docFreq=24, maxDocs=44218)
          0.046827413 = queryNorm
        0.3746787 = fieldWeight in 701, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          8.478011 = idf(docFreq=24, maxDocs=44218)
          0.03125 = fieldNorm(doc=701)
  0.5 = coord(2/4)

Content

Vgl.: http%3A%2F%2Fdigbib.ubka.uni-karlsruhe.de%2Fvolltexte%2Fdocuments%2F1627&ei=tAtYUYrBNoHKtQb3l4GYBw&usg=AFQjCNHeaxKkKU3-u54LWxMNYGXaaDLCGw&sig2=8WykXWQoDKjDSdGtAakH2Q&bvm=bv.44442042,d.Yms.

0.053777162 = product of:
  0.107554324 = sum of:
    0.0821189 = weight(_text_:data in 1638) [ClassicSimilarity], result of:
      0.0821189 = score(doc=1638,freq=14.0), product of:
        0.14807065 = queryWeight, product of:
          3.1620505 = idf(docFreq=5088, maxDocs=44218)
          0.046827413 = queryNorm
        0.55459267 = fieldWeight in 1638, product of:
          3.7416575 = tf(freq=14.0), with freq of:
            14.0 = termFreq=14.0
          3.1620505 = idf(docFreq=5088, maxDocs=44218)
          0.046875 = fieldNorm(doc=1638)
    0.025435425 = product of:
      0.05087085 = sum of:
        0.05087085 = weight(_text_:processing in 1638) [ClassicSimilarity], result of:
          0.05087085 = score(doc=1638,freq=2.0), product of:
            0.18956426 = queryWeight, product of:
              4.048147 = idf(docFreq=2097, maxDocs=44218)
              0.046827413 = queryNorm
            0.26835677 = fieldWeight in 1638, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              4.048147 = idf(docFreq=2097, maxDocs=44218)
              0.046875 = fieldNorm(doc=1638)
      0.5 = coord(1/2)
  0.5 = coord(2/4)

Abstract

The Web of Data keeps growing rapidly. However, the full exploitation of this large amount of structured data faces numerous challenges like usability, scalability, imprecise information needs and data change. We present Semplore, an IR-based system that aims at addressing these issues. Semplore supports intuitive faceted search and complex queries both on text and structured data. It combines imprecise keyword search and precise structured query in a unified ranking scheme. Scalable query processing is supported by leveraging inverted indexes traditionally used in IR systems. This is combined with a novel block-based index structure to support efficient index update when data changes. The experimental results show that Semplore is an efficient and effective system for searching the Web of Data and can be used as a basic infrastructure for Web-scale Semantic Web search engines.

0.047313843 = product of:
  0.094627686 = sum of:
    0.07242205 = weight(_text_:data in 2640) [ClassicSimilarity], result of:
      0.07242205 = score(doc=2640,freq=8.0), product of:
        0.14807065 = queryWeight, product of:
          3.1620505 = idf(docFreq=5088, maxDocs=44218)
          0.046827413 = queryNorm
        0.48910472 = fieldWeight in 2640, product of:
          2.828427 = tf(freq=8.0), with freq of:
            8.0 = termFreq=8.0
          3.1620505 = idf(docFreq=5088, maxDocs=44218)
          0.0546875 = fieldNorm(doc=2640)
    0.022205638 = product of:
      0.044411276 = sum of:
        0.044411276 = weight(_text_:22 in 2640) [ClassicSimilarity], result of:
          0.044411276 = score(doc=2640,freq=2.0), product of:
            0.16398162 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.046827413 = queryNorm
            0.2708308 = fieldWeight in 2640, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.0546875 = fieldNorm(doc=2640)
      0.5 = coord(1/2)
  0.5 = coord(2/4)

Abstract

Library catalogues contain an enormous amount of structured, high-quality data, however, this data is generally not made available to semantic web applications. In this paper we describe the tools and techniques used to make the Swedish Union Catalogue (LIBRIS) part of the Semantic Web and Linked Data. The focus is on links to and between resources and the mechanisms used to make data available, rather than perfect description of the individual resources. We also present a method of creating links between records of the same work.

Source

Metadata for semantic and social applications : proceedings of the International Conference on Dublin Core and Metadata Applications, Berlin, 22 - 26 September 2008, DC 2008: Berlin, Germany / ed. by Jane Greenberg and Wolfgang Klas

0.03670788 = product of:
  0.07341576 = sum of:
    0.051210128 = weight(_text_:data in 759) [ClassicSimilarity], result of:
      0.051210128 = score(doc=759,freq=4.0), product of:
        0.14807065 = queryWeight, product of:
          3.1620505 = idf(docFreq=5088, maxDocs=44218)
          0.046827413 = queryNorm
        0.34584928 = fieldWeight in 759, product of:
          2.0 = tf(freq=4.0), with freq of:
            4.0 = termFreq=4.0
          3.1620505 = idf(docFreq=5088, maxDocs=44218)
          0.0546875 = fieldNorm(doc=759)
    0.022205638 = product of:
      0.044411276 = sum of:
        0.044411276 = weight(_text_:22 in 759) [ClassicSimilarity], result of:
          0.044411276 = score(doc=759,freq=2.0), product of:
            0.16398162 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.046827413 = queryNorm
            0.2708308 = fieldWeight in 759, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.0546875 = fieldNorm(doc=759)
      0.5 = coord(1/2)
  0.5 = coord(2/4)

Abstract

XML will have a profound impact on the way data is exchanged on the Internet. An important feature of this language is the separation of content from presentation, which makes it easier to select and/or reformat the data. However, due to the likelihood of numerous industry and domain specific DTDs, those who wish to integrate information will still be faced with the problem of semantic interoperability. In this paper we discuss why this problem is not solved by XML, and then discuss why the Resource Description Framework is only a partial solution. We then present the SHOE language, which we feel has many of the features necessary to enable a semantic web, and describe an existing set of tools that make it easy to use the language.

Date

11. 5.2013 19:22:18

0.033820912 = product of:
  0.067641824 = sum of:
    0.050684877 = weight(_text_:data in 3000) [ClassicSimilarity], result of:
      0.050684877 = score(doc=3000,freq=12.0), product of:
        0.14807065 = queryWeight, product of:
          3.1620505 = idf(docFreq=5088, maxDocs=44218)
          0.046827413 = queryNorm
        0.342302 = fieldWeight in 3000, product of:
          3.4641016 = tf(freq=12.0), with freq of:
            12.0 = termFreq=12.0
          3.1620505 = idf(docFreq=5088, maxDocs=44218)
          0.03125 = fieldNorm(doc=3000)
    0.016956951 = product of:
      0.033913903 = sum of:
        0.033913903 = weight(_text_:processing in 3000) [ClassicSimilarity], result of:
          0.033913903 = score(doc=3000,freq=2.0), product of:
            0.18956426 = queryWeight, product of:
              4.048147 = idf(docFreq=2097, maxDocs=44218)
              0.046827413 = queryNorm
            0.17890452 = fieldWeight in 3000, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              4.048147 = idf(docFreq=2097, maxDocs=44218)
              0.03125 = fieldNorm(doc=3000)
      0.5 = coord(1/2)
  0.5 = coord(2/4)

Abstract

Six years ago in this magazine, Tim Berners-Lee, James Hendler and Ora Lassila unveiled a nascent vision of the Semantic Web: a highly interconnected network of data that could be easily accessed and understood by any desktop or handheld machine. They painted a future of intelligent software agents that would head out on the World Wide Web and automatically book flights and hotels for our trips, update our medical records and give us a single, customized answer to a particular question without our having to search for information or pore through results. They also presented the young technologies that would make this vision come true: a common language for representing data that could be understood by all kinds of software agents; ontologies--sets of statements--that translate information from disparate databases into common terms; and rules that allow software agents to reason about the information described in those terms. The data format, ontologies and reasoning software would operate like one big application on the World Wide Web, analyzing all the raw data stored in online databases as well as all the data about the text, images, video and communications the Web contained. Like the Web itself, the Semantic Web would grow in a grassroots fashion, only this time aided by working groups within the World Wide Web Consortium, which helps to advance the global medium. Since then skeptics have said the Semantic Web would be too difficult for people to understand or exploit. Not so. The enabling technologies have come of age. A vibrant community of early adopters has agreed on standards that have steadily made the Semantic Web practical to use. Large companies have major projects under way that will greatly improve the efficiencies of in-house operations and of scientific research. Other firms are using the Semantic Web to enhance business-to-business interactions and to build the hidden data-processing structures, or back ends, behind new consumer services. And like an iceberg, the tip of this large body of work is emerging in direct consumer applications, too.

0.0295933 = product of:
  0.0591866 = sum of:
    0.044349268 = weight(_text_:data in 3062) [ClassicSimilarity], result of:
      0.044349268 = score(doc=3062,freq=12.0), product of:
        0.14807065 = queryWeight, product of:
          3.1620505 = idf(docFreq=5088, maxDocs=44218)
          0.046827413 = queryNorm
        0.29951423 = fieldWeight in 3062, product of:
          3.4641016 = tf(freq=12.0), with freq of:
            12.0 = termFreq=12.0
          3.1620505 = idf(docFreq=5088, maxDocs=44218)
          0.02734375 = fieldNorm(doc=3062)
    0.014837332 = product of:
      0.029674664 = sum of:
        0.029674664 = weight(_text_:processing in 3062) [ClassicSimilarity], result of:
          0.029674664 = score(doc=3062,freq=2.0), product of:
            0.18956426 = queryWeight, product of:
              4.048147 = idf(docFreq=2097, maxDocs=44218)
              0.046827413 = queryNorm
            0.15654145 = fieldWeight in 3062, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              4.048147 = idf(docFreq=2097, maxDocs=44218)
              0.02734375 = fieldNorm(doc=3062)
      0.5 = coord(1/2)
  0.5 = coord(2/4)

Abstract

18 August 2009 -- Today W3C announces a new standard that builds a bridge between the world of knowledge organization systems - including thesauri, classifications, subject headings, taxonomies, and folksonomies - and the linked data community, bringing benefits to both. Libraries, museums, newspapers, government portals, enterprises, social networking applications, and other communities that manage large collections of books, historical artifacts, news reports, business glossaries, blog entries, and other items can now use Simple Knowledge Organization System (SKOS) to leverage the power of linked data. As different communities with expertise and established vocabularies use SKOS to integrate them into the Semantic Web, they increase the value of the information for everyone.

Content

SKOS Adapts to the Diversity of Knowledge Organization Systems A useful starting point for understanding the role of SKOS is the set of subject headings published by the US Library of Congress (LOC) for categorizing books, videos, and other library resources. These headings can be used to broaden or narrow queries for discovering resources. For instance, one can narrow a query about books on "Chinese literature" to "Chinese drama," or further still to "Chinese children's plays." Library of Congress subject headings have evolved within a community of practice over a period of decades. By now publishing these subject headings in SKOS, the Library of Congress has made them available to the linked data community, which benefits from a time-tested set of concepts to re-use in their own data. This re-use adds value ("the network effect") to the collection. When people all over the Web re-use the same LOC concept for "Chinese drama," or a concept from some other vocabulary linked to it, this creates many new routes to the discovery of information, and increases the chances that relevant items will be found. As an example of mapping one vocabulary to another, a combined effort from the STITCH, TELplus and MACS Projects provides links between LOC concepts and RAMEAU, a collection of French subject headings used by the Bibliothèque Nationale de France and other institutions. SKOS can be used for subject headings but also many other approaches to organizing knowledge. Because different communities are comfortable with different organization schemes, SKOS is designed to port diverse knowledge organization systems to the Web. "Active participation from the library and information science community in the development of SKOS over the past seven years has been key to ensuring that SKOS meets a variety of needs," said Thomas Baker, co-chair of the Semantic Web Deployment Working Group, which published SKOS. "One goal in creating SKOS was to provide new uses for well-established knowledge organization systems by providing a bridge to the linked data cloud." SKOS is part of the Semantic Web technology stack. Like the Web Ontology Language (OWL), SKOS can be used to define vocabularies. But the two technologies were designed to meet different needs. SKOS is a simple language with just a few features, tuned for sharing and linking knowledge organization systems such as thesauri and classification schemes. OWL offers a general and powerful framework for knowledge representation, where additional "rigor" can afford additional benefits (for instance, business rule processing). To get started with SKOS, see the SKOS Primer.

0.025605064 = product of:
  0.102420256 = sum of:
    0.102420256 = weight(_text_:data in 3791) [ClassicSimilarity], result of:
      0.102420256 = score(doc=3791,freq=16.0), product of:
        0.14807065 = queryWeight, product of:
          3.1620505 = idf(docFreq=5088, maxDocs=44218)
          0.046827413 = queryNorm
        0.69169855 = fieldWeight in 3791, product of:
          4.0 = tf(freq=16.0), with freq of:
            16.0 = termFreq=16.0
          3.1620505 = idf(docFreq=5088, maxDocs=44218)
          0.0546875 = fieldNorm(doc=3791)
  0.25 = coord(1/4)

Abstract

This document provides a tutorial on how to publish Linked Data on the Web. After a general overview of the concept of Linked Data, we describe several practical recipes for publishing information as Linked Data on the Web.

Content

This tutorial has been superseeded by the book Linked Data: Evolving the Web into a Global Data Space written by Tom Heath and Christian Bizer. This tutorial was published in 2007 and is still online for historical reasons. The Linked Data book was published in 2011 and provides a more detailed and up-to-date introduction into Linked Data.

0.025035713 = product of:
  0.050071426 = sum of:
    0.031038022 = weight(_text_:data in 2556) [ClassicSimilarity], result of:
      0.031038022 = score(doc=2556,freq=2.0), product of:
        0.14807065 = queryWeight, product of:
          3.1620505 = idf(docFreq=5088, maxDocs=44218)
          0.046827413 = queryNorm
        0.2096163 = fieldWeight in 2556, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          3.1620505 = idf(docFreq=5088, maxDocs=44218)
          0.046875 = fieldNorm(doc=2556)
    0.019033402 = product of:
      0.038066804 = sum of:
        0.038066804 = weight(_text_:22 in 2556) [ClassicSimilarity], result of:
          0.038066804 = score(doc=2556,freq=2.0), product of:
            0.16398162 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.046827413 = queryNorm
            0.23214069 = fieldWeight in 2556, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.046875 = fieldNorm(doc=2556)
      0.5 = coord(1/2)
  0.5 = coord(2/4)

Abstract

First generation scholarly research on the Web lacked a firm system of authority control. Second generation Web research is beginning to model subject access with library science principles of bibliographic control and cataloguing. Harnessing the Web and organising the intellectual content with standards and controlled vocabulary provides precise search and retrieval capability, increasing relevance and efficient use of technology. Dublin Core metadata standards permit a full evaluation and cataloguing of Web resources appropriate to highly specific research needs and discovery. Current research points to a type of structure based on a system of faceted classification. This system allows the semantic and syntactic relationships to be defined. Controlled vocabulary, such as the Library of Congress Subject Headings, can be assigned, not in a hierarchical structure, but rather as descriptive facets of relating concepts. Web design features such as this are adding value to discovery and filtering out data that lack authority. The system design allows for scalability and extensibility, two technical features that are integral to future development of the digital library and resource discovery.

Date

30.12.2008 18:22:46

0.023530604 = product of:
  0.04706121 = sum of:
    0.02586502 = weight(_text_:data in 2069) [ClassicSimilarity], result of:
      0.02586502 = score(doc=2069,freq=2.0), product of:
        0.14807065 = queryWeight, product of:
          3.1620505 = idf(docFreq=5088, maxDocs=44218)
          0.046827413 = queryNorm
        0.17468026 = fieldWeight in 2069, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          3.1620505 = idf(docFreq=5088, maxDocs=44218)
          0.0390625 = fieldNorm(doc=2069)
    0.021196188 = product of:
      0.042392377 = sum of:
        0.042392377 = weight(_text_:processing in 2069) [ClassicSimilarity], result of:
          0.042392377 = score(doc=2069,freq=2.0), product of:
            0.18956426 = queryWeight, product of:
              4.048147 = idf(docFreq=2097, maxDocs=44218)
              0.046827413 = queryNorm
            0.22363065 = fieldWeight in 2069, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              4.048147 = idf(docFreq=2097, maxDocs=44218)
              0.0390625 = fieldNorm(doc=2069)
      0.5 = coord(1/2)
  0.5 = coord(2/4)

Abstract

The semantic web not only contains resources but also includes the heterogeneous relationships among them, which is sharply distinguished from the current web. As the growth of the semantic web, specialized search techniques are of significance. In this paper, we present RSS-a framework for enabling ranked semantic search on the semantic web. In this framework, the heterogeneity of relationships is fully exploited to determine the global importance of resources. In addition, the search results can be greatly expanded with entities most semantically related to the query, thus able to provide users with properly ordered semantic search results by combining global ranking values and the relevance between the resources and the query. The proposed semantic search model which supports inference is very different from traditional keyword-based search methods. Moreover, RSS also distinguishes from many current methods of accessing the semantic web data in that it applies novel ranking strategies to prevent returning search results in disorder. The experimental results show that the framework is feasible and can produce better ordering of semantic search results than directly applying the standard PageRank algorithm on the semantic web.

Source

Information processing and management. 44(2008) no.2, S.893-909

0.019398764 = product of:
  0.077595055 = sum of:
    0.077595055 = weight(_text_:data in 1643) [ClassicSimilarity], result of:
      0.077595055 = score(doc=1643,freq=18.0), product of:
        0.14807065 = queryWeight, product of:
          3.1620505 = idf(docFreq=5088, maxDocs=44218)
          0.046827413 = queryNorm
        0.52404076 = fieldWeight in 1643, product of:
          4.2426405 = tf(freq=18.0), with freq of:
            18.0 = termFreq=18.0
          3.1620505 = idf(docFreq=5088, maxDocs=44218)
          0.0390625 = fieldNorm(doc=1643)
  0.25 = coord(1/4)

Abstract

The DBpedia project is a community effort to extract structured information from Wikipedia and to make this information accessible on the Web. The resulting DBpedia knowledge base currently describes over 2.6 million entities. For each of these entities, DBpedia defines a globally unique identifier that can be dereferenced over the Web into a rich RDF description of the entity, including human-readable definitions in 30 languages, relationships to other resources, classifications in four concept hierarchies, various facts as well as data-level links to other Web data sources describing the entity. Over the last year, an increasing number of data publishers have begun to set data-level links to DBpedia resources, making DBpedia a central interlinking hub for the emerging Web of data. Currently, the Web of interlinked data sources around DBpedia provides approximately 4.7 billion pieces of information and covers domains suc as geographic information, people, companies, films, music, genes, drugs, books, and scientific publications. This article describes the extraction of the DBpedia knowledge base, the current status of interlinking DBpedia with other data sources on the Web, and gives an overview of applications that facilitate the Web of Data around DBpedia.

0.01835394 = product of:
  0.03670788 = sum of:
    0.025605064 = weight(_text_:data in 2665) [ClassicSimilarity], result of:
      0.025605064 = score(doc=2665,freq=4.0), product of:
        0.14807065 = queryWeight, product of:
          3.1620505 = idf(docFreq=5088, maxDocs=44218)
          0.046827413 = queryNorm
        0.17292464 = fieldWeight in 2665, product of:
          2.0 = tf(freq=4.0), with freq of:
            4.0 = termFreq=4.0
          3.1620505 = idf(docFreq=5088, maxDocs=44218)
          0.02734375 = fieldNorm(doc=2665)
    0.011102819 = product of:
      0.022205638 = sum of:
        0.022205638 = weight(_text_:22 in 2665) [ClassicSimilarity], result of:
          0.022205638 = score(doc=2665,freq=2.0), product of:
            0.16398162 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.046827413 = queryNorm
            0.1354154 = fieldWeight in 2665, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.02734375 = fieldNorm(doc=2665)
      0.5 = coord(1/2)
  0.5 = coord(2/4)

Abstract

Platforms for social computing connect users via shared references to people with whom they have relationships, events attended, places lived in or traveled to, and topics such as favorite books or movies. Since free text is insufficient for expressing such references precisely and unambiguously, many social computing platforms coin identifiers for topics, places, events, and people and provide interfaces for finding and selecting these identifiers from controlled lists. Using these interfaces, users collaboratively construct a web of links among entities. This model needn't be limited to social networking sites. Understanding an item in a digital library or museum requires context: information about the topics, places, events, and people to which the item is related. Students, journalists and investigators traditionally discover this kind of context by asking "the four Ws": what, where, when and who. The DCMI Kernel Metadata Community has recognized the four Ws as fundamental elements of descriptions (Kunze & Turner, 2007). Making better use of metadata to answer these questions via links to appropriate contextual resources has been our focus in a series of research projects over the past few years. Currently we are building a system for enabling readers of any text to relate any topic, place, event or person mentioned in the text to the best explanatory resources available. This system is being developed with two different corpora: a diverse variety of biographical texts characterized by very rich and dense mentions of people, events, places and activities, and a large collection of newly-scanned books, journals and manuscripts relating to Irish culture and history. Like a social computing platform, our system consists of tools for referring to topics, places, events or people, disambiguating these references by linking them to unique identifiers, and using the disambiguated references to provide useful information in context and to link to related resources. Yet current social computing platforms, while usually amenable to importing and exporting data, tend to mint proprietary identifiers and expect links to be traversed using their own interfaces. We take a different approach, using identifiers from both established and emerging naming authorities, representing relationships using standardized metadata vocabularies, and publishing those representations using standard protocols so that links can be stored and traversed anywhere. Central to our strategy is to move from appearances in a text to naming authorities to the the construction of links for searching or querying trusted resources. Using identifiers from naming authorities, rather than literal values (as in the DCMI Kernel) or keys from a proprietary database, makes it more likely that links constructed using our system will continue to be useful in the future. WorldCat Identities URIs (http://worldcat.org/identities/) linked to Library of Congress and Deutsche Nationalbibliothek authority files for persons and organizations and Geonames (http://geonames.org/) URIs for places are stable identifiers attached to a wealth of useful metadata. Yet no naming authority can be totally comprehensive, so our system can be extended to use new sources of identifiers as needed. For example, we are experimenting with using Freebase (http://freebase.com/) URIs to identify historical events, for which no established naming authority currently exists. Stable identifiers (URIs), standardized hyperlinked data formats (XML), and uniform publishing protocols (HTTP) are key ingredients of the web's open architecture. Our system provides an example of how this open architecture can be exploited to build flexible and useful tools for connecting resources via shared references to topics, places, events, and people.

Source

Metadata for semantic and social applications : proceedings of the International Conference on Dublin Core and Metadata Applications, Berlin, 22 - 26 September 2008, DC 2008: Berlin, Germany / ed. by Jane Greenberg and Wolfgang Klas

0.016690476 = product of:
  0.03338095 = sum of:
    0.020692015 = weight(_text_:data in 2661) [ClassicSimilarity], result of:
      0.020692015 = score(doc=2661,freq=2.0), product of:
        0.14807065 = queryWeight, product of:
          3.1620505 = idf(docFreq=5088, maxDocs=44218)
          0.046827413 = queryNorm
        0.1397442 = fieldWeight in 2661, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          3.1620505 = idf(docFreq=5088, maxDocs=44218)
          0.03125 = fieldNorm(doc=2661)
    0.012688936 = product of:
      0.025377871 = sum of:
        0.025377871 = weight(_text_:22 in 2661) [ClassicSimilarity], result of:
          0.025377871 = score(doc=2661,freq=2.0), product of:
            0.16398162 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.046827413 = queryNorm
            0.15476047 = fieldWeight in 2661, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.03125 = fieldNorm(doc=2661)
      0.5 = coord(1/2)
  0.5 = coord(2/4)

Abstract

The basic goal of education within a discipline is to transform a novice into an expert. This entails moving the novice toward the "semantic space" that the expert inhabits-the space of concepts, meanings, vocabularies, and other intellectual constructs that comprise the discipline. Metadata is significant to this goal in digitally mediated education environments. Encoding the experts' semantic space not only enables the sharing of semantics among discipline scientists, but also creates an environment that bridges the semantic gap between the common vocabulary of the novice and the granular descriptive language of the seasoned scientist (Greenberg, et al, 2005). Developments underlying the Semantic Web, where vocabularies are formalized in the Web Ontology Language (OWL), and Web 2.0 approaches of user-generated folksonomies provide an infrastructure for linking vocabulary systems and promoting group learning via metadata literacy. Group learning is a pedagogical approach to teaching that harnesses the phenomenon of "collective intelligence" to increase learning by means of collaboration. Learning a new semantic system can be daunting for a novice, and yet it is integral to advance one's knowledge in a discipline and retain interest. These ideas are key to the "BOT 2.0: Botany through Web 2.0, the Memex and Social Learning" project (Bot 2.0).72 Bot 2.0 is a collaboration involving the North Carolina Botanical Garden, the UNC SILS Metadata Research center, and the Renaissance Computing Institute (RENCI). Bot 2.0 presents a curriculum utilizing a memex as a way for students to link and share digital information, working asynchronously in an environment beyond the traditional classroom. Our conception of a memex is not a centralized black box but rather a flexible, distributed framework that uses the most salient and easiest-to-use collaborative platforms (e.g., Facebook, Flickr, wiki and blog technology) for personal information management. By meeting students "where they live" digitally, we hope to attract students to the study of botanical science. A key aspect is to teach students scientific terminology and about the value of metadata, an inherent function in several of the technologies and in the instructional approach we are utilizing. This poster will report on a study examining the value of both folksonomies and taxonomies for post-secondary college students learning plant identification. Our data is drawn from a curriculum involving a virtual independent learning portion and a "BotCamp" weekend at UNC, where students work with digital plan specimens that they have captured. Results provide some insight into the importance of collaboration and shared vocabulary for gaining confidence and for student progression from novice to expert in botany.

Source

Metadata for semantic and social applications : proceedings of the International Conference on Dublin Core and Metadata Applications, Berlin, 22 - 26 September 2008, DC 2008: Berlin, Germany / ed. by Jane Greenberg and Wolfgang Klas

0.016471423 = product of:
  0.032942846 = sum of:
    0.018105512 = weight(_text_:data in 1981) [ClassicSimilarity], result of:
      0.018105512 = score(doc=1981,freq=2.0), product of:
        0.14807065 = queryWeight, product of:
          3.1620505 = idf(docFreq=5088, maxDocs=44218)
          0.046827413 = queryNorm
        0.12227618 = fieldWeight in 1981, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          3.1620505 = idf(docFreq=5088, maxDocs=44218)
          0.02734375 = fieldNorm(doc=1981)
    0.014837332 = product of:
      0.029674664 = sum of:
        0.029674664 = weight(_text_:processing in 1981) [ClassicSimilarity], result of:
          0.029674664 = score(doc=1981,freq=2.0), product of:
            0.18956426 = queryWeight, product of:
              4.048147 = idf(docFreq=2097, maxDocs=44218)
              0.046827413 = queryNorm
            0.15654145 = fieldWeight in 1981, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              4.048147 = idf(docFreq=2097, maxDocs=44218)
              0.02734375 = fieldNorm(doc=1981)
      0.5 = coord(1/2)
  0.5 = coord(2/4)

Abstract

As the World Wide Web continues to expand, it becomes increasingly difficult for users to obtain information efficiently. Because most search engines read format languages such as HTML or SGML, search results reflect formatting tags more than actual page content, which is expressed in natural language. Spinning the Semantic Web describes an exciting new type of hierarchy and standardization that will replace the current "Web of links" with a "Web of meaning." Using a flexible set of languages and tools, the Semantic Web will make all available information - display elements, metadata, services, images, and especially content - accessible. The result will be an immense repository of information accessible for a wide range of new applications. This first handbook for the Semantic Web covers, among other topics, software agents that can negotiate and collect information, markup languages that can tag many more types of information in a document, and knowledge systems that enable machines to read Web pages and determine their reliability. The truly interdisciplinary Semantic Web combines aspects of artificial intelligence, markup languages, natural language processing, information retrieval, knowledge representation, intelligent agents, and databases.

Content

Inhalt: Tim Bemers-Lee: The Original Dream - Re-enter Machines - Where Are We Now? - The World Wide Web Consortium - Where Is the Web Going Next? / Dieter Fensel, James Hendler, Henry Lieberman, and Wolfgang Wahlster: Why Is There a Need for the Semantic Web and What Will It Provide? - How the Semantic Web Will Be Possible / Jeff Heflin, James Hendler, and Sean Luke: SHOE: A Blueprint for the Semantic Web / Deborah L. McGuinness, Richard Fikes, Lynn Andrea Stein, and James Hendler: DAML-ONT: An Ontology Language for the Semantic Web / Michel Klein, Jeen Broekstra, Dieter Fensel, Frank van Harmelen, and Ian Horrocks: Ontologies and Schema Languages on the Web / Borys Omelayenko, Monica Crubezy, Dieter Fensel, Richard Benjamins, Bob Wielinga, Enrico Motta, Mark Musen, and Ying Ding: UPML: The Language and Tool Support for Making the Semantic Web Alive / Deborah L. McGuinness: Ontologies Come of Age / Jeen Broekstra, Arjohn Kampman, and Frank van Harmelen: Sesame: An Architecture for Storing and Querying RDF Data and Schema Information / Rob Jasper and Mike Uschold: Enabling Task-Centered Knowledge Support through Semantic Markup / Yolanda Gil: Knowledge Mobility: Semantics for the Web as a White Knight for Knowledge-Based Systems / Sanjeev Thacker, Amit Sheth, and Shuchi Patel: Complex Relationships for the Semantic Web / Alexander Maedche, Steffen Staab, Nenad Stojanovic, Rudi Studer, and York Sure: SEmantic portAL: The SEAL Approach / Ora Lassila and Mark Adler: Semantic Gadgets: Ubiquitous Computing Meets the Semantic Web / Christopher Frye, Mike Plusch, and Henry Lieberman: Static and Dynamic Semantics of the Web / Masahiro Hori: Semantic Annotation for Web Content Adaptation / Austin Tate, Jeff Dalton, John Levine, and Alex Nixon: Task-Achieving Agents on the World Wide Web

0.013686483 = product of:
  0.05474593 = sum of:
    0.05474593 = weight(_text_:data in 2477) [ClassicSimilarity], result of:
      0.05474593 = score(doc=2477,freq=14.0), product of:
        0.14807065 = queryWeight, product of:
          3.1620505 = idf(docFreq=5088, maxDocs=44218)
          0.046827413 = queryNorm
        0.36972845 = fieldWeight in 2477, product of:
          3.7416575 = tf(freq=14.0), with freq of:
            14.0 = termFreq=14.0
          3.1620505 = idf(docFreq=5088, maxDocs=44218)
          0.03125 = fieldNorm(doc=2477)
  0.25 = coord(1/4)

Abstract

This book constitutes the refereed proceedings of the joint 6th International Semantic Web Conference, ISWC 2007, and the 2nd Asian Semantic Web Conference, ASWC 2007, held in Busan, Korea, in November 2007. The 50 revised full academic papers and 12 revised application papers presented together with 5 Semantic Web Challenge papers and 12 selected doctoral consortium articles were carefully reviewed and selected from a total of 257 submitted papers to the academic track and 29 to the applications track. The papers address all current issues in the field of the semantic Web, ranging from theoretical and foundational aspects to various applied topics such as management of semantic Web data, ontologies, semantic Web architecture, social semantic Web, as well as applications of the semantic Web. Short descriptions of the top five winning applications submitted to the Semantic Web Challenge competition conclude the volume.

LCSH

Data mining
Data Mining and Knowledge Discovery

RSWK

Semantic Web / Metadatenmodell / Data Mining / Ontologie <Wissensverarbeitung> / Kongress / Pusan <2007> (BVB)

Subject

Data mining
Data Mining and Knowledge Discovery
Semantic Web / Metadatenmodell / Data Mining / Ontologie <Wissensverarbeitung> / Kongress / Pusan <2007> (BVB)

0.013439858 = product of:
  0.053759433 = sum of:
    0.053759433 = weight(_text_:data in 4260) [ClassicSimilarity], result of:
      0.053759433 = score(doc=4260,freq=6.0), product of:
        0.14807065 = queryWeight, product of:
          3.1620505 = idf(docFreq=5088, maxDocs=44218)
          0.046827413 = queryNorm
        0.3630661 = fieldWeight in 4260, product of:
          2.4494898 = tf(freq=6.0), with freq of:
            6.0 = termFreq=6.0
          3.1620505 = idf(docFreq=5088, maxDocs=44218)
          0.046875 = fieldNorm(doc=4260)
  0.25 = coord(1/4)

Abstract

DBpedia is a community effort to extract structured information from Wikipedia and to make this information available on the Web. DBpedia allows you to ask sophisticated queries against datasets derived from Wikipedia and to link other datasets on the Web to Wikipedia data. We describe the extraction of the DBpedia datasets, and how the resulting information is published on the Web for human- and machineconsumption. We describe some emerging applications from the DBpedia community and show how website authors can facilitate DBpedia content within their sites. Finally, we present the current status of interlinking DBpedia with other open datasets on the Web and outline how DBpedia could serve as a nucleus for an emerging Web of open data.

0.013439858 = product of:
  0.053759433 = sum of:
    0.053759433 = weight(_text_:data in 4688) [ClassicSimilarity], result of:
      0.053759433 = score(doc=4688,freq=6.0), product of:
        0.14807065 = queryWeight, product of:
          3.1620505 = idf(docFreq=5088, maxDocs=44218)
          0.046827413 = queryNorm
        0.3630661 = fieldWeight in 4688, product of:
          2.4494898 = tf(freq=6.0), with freq of:
            6.0 = termFreq=6.0
          3.1620505 = idf(docFreq=5088, maxDocs=44218)
          0.046875 = fieldNorm(doc=4688)
  0.25 = coord(1/4)

Abstract

This document defines the Simple Knowledge Organization System (SKOS), a common data model for sharing and linking knowledge organization systems via the Web. Many knowledge organization systems, such as thesauri, taxonomies, classification schemes and subject heading systems, share a similar structure, and are used in similar applications. SKOS captures much of this similarity and makes it explicit, to enable data and technology sharing across diverse applications. The SKOS data model provides a standard, low-cost migration path for porting existing knowledge organization systems to the Semantic Web. SKOS also provides a lightweight, intuitive language for developing and sharing new knowledge organization systems. It may be used on its own, or in combination with formal knowledge representation languages such as the Web Ontology language (OWL). This document is the normative specification of the Simple Knowledge Organization System. It is intended for readers who are involved in the design and implementation of information systems, and who already have a good understanding of Semantic Web technology, especially RDF and OWL. For an informative guide to using SKOS, see the [SKOS-PRIMER].

0.012802532 = product of:
  0.051210128 = sum of:
    0.051210128 = weight(_text_:data in 1541) [ClassicSimilarity], result of:
      0.051210128 = score(doc=1541,freq=4.0), product of:
        0.14807065 = queryWeight, product of:
          3.1620505 = idf(docFreq=5088, maxDocs=44218)
          0.046827413 = queryNorm
        0.34584928 = fieldWeight in 1541, product of:
          2.0 = tf(freq=4.0), with freq of:
            4.0 = termFreq=4.0
          3.1620505 = idf(docFreq=5088, maxDocs=44218)
          0.0546875 = fieldNorm(doc=1541)
  0.25 = coord(1/4)

Abstract

The next major advance in the Web-Web 3.0-will be built on semantic Web technologies, which will allow data to be shared and reused across application, enterprise, and community boundaries. Written by a team of highly experienced Web developers, this book explains examines how this powerful new technology can unify and fully leverage the ever-growing data, information, and services that are available on the Internet. Helpful examples demonstrate how to use the semantic Web to solve practical, real-world problems while you take a look at the set of design principles, collaborative working groups, and technologies that form the semantic Web. The companion Web site features full code, as well as a reference section, a FAQ section, a discussion forum, and a semantic blog.

0.012802532 = product of:
  0.051210128 = sum of:
    0.051210128 = weight(_text_:data in 3871) [ClassicSimilarity], result of:
      0.051210128 = score(doc=3871,freq=4.0), product of:
        0.14807065 = queryWeight, product of:
          3.1620505 = idf(docFreq=5088, maxDocs=44218)
          0.046827413 = queryNorm
        0.34584928 = fieldWeight in 3871, product of:
          2.0 = tf(freq=4.0), with freq of:
            4.0 = termFreq=4.0
          3.1620505 = idf(docFreq=5088, maxDocs=44218)
          0.0546875 = fieldNorm(doc=3871)
  0.25 = coord(1/4)

Abstract

The "semantic web (SW)" is a vision of a web of linked data, allowing querying, integration, and sharing of data from distributed sources in heterogeneous formats, using ontologies to provide an associated and explicit semantic interpretation. This entry describes the series of layered formalisms and standards that underlie this vision, and chronicles their historical and ongoing development. A number of applications, scientific and otherwise, academic and commercial, are reviewed. The SW has often been a controversial enterprise, and some of the controversies are reviewed, and misconceptions defused.

0.012167135 = product of:
  0.04866854 = sum of:
    0.04866854 = sum of:
      0.021196188 = weight(_text_:processing in 150) [ClassicSimilarity], result of:
        0.021196188 = score(doc=150,freq=2.0), product of:
          0.18956426 = queryWeight, product of:
            4.048147 = idf(docFreq=2097, maxDocs=44218)
            0.046827413 = queryNorm
          0.111815326 = fieldWeight in 150, product of:
            1.4142135 = tf(freq=2.0), with freq of:
              2.0 = termFreq=2.0
            4.048147 = idf(docFreq=2097, maxDocs=44218)
            0.01953125 = fieldNorm(doc=150)
      0.027472353 = weight(_text_:22 in 150) [ClassicSimilarity], result of:
        0.027472353 = score(doc=150,freq=6.0), product of:
          0.16398162 = queryWeight, product of:
            3.5018296 = idf(docFreq=3622, maxDocs=44218)
            0.046827413 = queryNorm
          0.16753313 = fieldWeight in 150, product of:
            2.4494898 = tf(freq=6.0), with freq of:
              6.0 = termFreq=6.0
            3.5018296 = idf(docFreq=3622, maxDocs=44218)
            0.01953125 = fieldNorm(doc=150)
  0.25 = coord(1/4)

Classification

006.7 22

Date

7. 3.2007 19:30:22

DDC

006.7 22

Footnote

The final part of the book discusses research in multimedia content management systems and the semantic web, and presents examples and applications for semantic multimedia analysis in search and retrieval systems. These chapters describe example systems in which current projects have been implemented, and include extensive results and real demonstrations. For example, real case scenarios such as ECommerce medical applications and Web services have been introduced. Topics in natural language, speech and image processing techniques and their application for multimedia indexing, and content-based retrieval have been elaborated upon with extensive examples and deployment methods. The editors of the book themselves provide the readers with a chapter about their latest research results on knowledge-based multimedia content indexing and retrieval. Some interesting applications for multimedia content and the semantic web are introduced. Applications that have taken advantage of the metadata provided by MPEG7 in order to realize advance-access services for multimedia content have been provided. The applications discussed in the third part of the book provide useful guidance to researchers and practitioners properly planning to implement semantic multimedia analysis techniques in new research and development projects in both academia and industry. A fourth part should be added to this book: performance measurements for integrated approaches of multimedia analysis and the semantic web. Performance of the semantic approach is a very sophisticated issue and requires extensive elaboration and effort. Measuring the semantic search is an ongoing research area; several chapters concerning performance measurement and analysis would be required to adequately cover this area and introduce it to readers."

0.011199882 = product of:
  0.04479953 = sum of:
    0.04479953 = weight(_text_:data in 231) [ClassicSimilarity], result of:
      0.04479953 = score(doc=231,freq=6.0), product of:
        0.14807065 = queryWeight, product of:
          3.1620505 = idf(docFreq=5088, maxDocs=44218)
          0.046827413 = queryNorm
        0.30255508 = fieldWeight in 231, product of:
          2.4494898 = tf(freq=6.0), with freq of:
            6.0 = termFreq=6.0
          3.1620505 = idf(docFreq=5088, maxDocs=44218)
          0.0390625 = fieldNorm(doc=231)
  0.25 = coord(1/4)

Abstract

As an extension to the current Web, Semantic Web will not only contain structured data with machine understandable semantics but also textual information. While structured queries can be used to find information more precisely on the Semantic Web, keyword searches are still needed to help exploit textual information. It thus becomes very important that we can combine precise structured queries with imprecise keyword searches to have a hybrid query capability. In addition, due to the huge volume of information on the Semantic Web, the hybrid query must be processed in a very scalable way. In this paper, we define such a hybrid query capability that combines unary tree-shaped structured queries with keyword searches. We show how existing information retrieval (IR) index structures and functions can be reused to index semantic web data and its textual information, and how the hybrid query is evaluated on the index structure using IR engines in an efficient and scalable manner. We implemented this IR approach in an engine called Semplore. Comprehensive experiments on its performance show that it is a promising approach. It leads us to believe that it may be possible to evolve current web search engines to query and search the Semantic Web. Finally, we briefy describe how Semplore is used for searching Wikipedia and an IBM customer's product information.