Search (2 results, page 1 of 1)

0.015562538 = product of:
  0.031125076 = sum of:
    0.031125076 = product of:
      0.062250152 = sum of:
        0.062250152 = weight(_text_:language in 468) [ClassicSimilarity], result of:
          0.062250152 = score(doc=468,freq=16.0), product of:
            0.2030952 = queryWeight, product of:
              3.9232929 = idf(docFreq=2376, maxDocs=44218)
              0.051766515 = queryNorm
            0.30650726 = fieldWeight in 468, product of:
              4.0 = tf(freq=16.0), with freq of:
                16.0 = termFreq=16.0
              3.9232929 = idf(docFreq=2376, maxDocs=44218)
              0.01953125 = fieldNorm(doc=468)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Abstract

The development of the Semantic Web, with machine-readable content, has the potential to revolutionise the World Wide Web and its use. A Semantic Web Primer provides an introduction and guide to this emerging field, describing its key ideas, languages and technologies. Suitable for use as a textbook or for self-study by professionals, it concentrates on undergraduate-level fundamental concepts and techniques that will enable readers to proceed with building applications on their own. It includes exercises, project descriptions and annotated references to relevant online materials. A Semantic Web Primer is the only available book on the Semantic Web to include a systematic treatment of the different languages (XML, RDF, OWL and rules) and technologies (explicit metadata, ontologies and logic and interference) that are central to Semantic Web development. The book also examines such crucial related topics as ontology engineering and application scenarios. After an introductory chapter, topics covered in succeeding chapters include XML and related technologies that support semantic interoperability; RDF and RDF Schema, the standard data model for machine-processable semantics; and OWL, the W3C-approved standard for a Web ontology language more extensive than RDF Schema; rules, both monotonic and nonmonotonic, in the framework of the Semantic Web; selected application domains and how the Semantic Web would benefit them; the development of ontology-based systems; and current debates on key issues and predictions for the future.

Footnote

The next chapter introduces resource description framework (RDF) and RDF schema (RDFS). Unlike XML, RDF provides a foundation for expressing the semantics of dada: it is a standard dada model for machine-processable semantics. Resource description framework schema offers a number of modeling primitives for organizing RDF vocabularies in typed hierarchies. In addition to RDF and RDFS, a query language for RDF, i.e. RQL. is introduced. This chapter and the next chapter are two of the most important chapters in the book. Chapter 4 presents another language called Web Ontology Language (OWL). Because RDFS is quite primitive as a modeling language for the Web, more powerful languages are needed. A richer language. DAML+OIL, is thus proposed as a joint endeavor of the United States and Europe. OWL takes DAML+OIL as the starting point, and aims to be the standardized and broadly accepted ontology language. At the beginning of the chapter, the nontrivial relation with RDF/RDFS is discussed. Then the authors describe the various language elements of OWL in some detail. Moreover, Appendix A contains an abstract OWL syntax. which compresses OWL and makes OWL much easier to read. Chapter 5 covers both monotonic and nonmonotonic rules. Whereas the previous chapter's mainly concentrate on specializations of knowledge representation, this chapter depicts the foundation of knowledge representation and inference. Two examples are also givwn to explain monotonic and non-monotonic rules, respectively. "To get the most out of the chapter. readers had better gain a thorough understanding of predicate logic first. Chapter 6 presents several realistic application scenarios to which the Semantic Web technology can be applied. including horizontal information products at Elsevier, data integration at Audi, skill finding at Swiss Life, a think tank portal at EnerSearch, e-learning. Web services, multimedia collection indexing, online procurement, raid device interoperability. These case studies give us some real feelings about the Semantic Web.

0.00953007 = product of:
  0.01906014 = sum of:
    0.01906014 = product of:
      0.03812028 = sum of:
        0.03812028 = weight(_text_:language in 636) [ClassicSimilarity], result of:
          0.03812028 = score(doc=636,freq=6.0), product of:
            0.2030952 = queryWeight, product of:
              3.9232929 = idf(docFreq=2376, maxDocs=44218)
              0.051766515 = queryNorm
            0.1876966 = fieldWeight in 636, product of:
              2.4494898 = tf(freq=6.0), with freq of:
                6.0 = termFreq=6.0
              3.9232929 = idf(docFreq=2376, maxDocs=44218)
              0.01953125 = fieldNorm(doc=636)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Abstract

The Text REtrieval Conference (TREC), a yearly workshop hosted by the US government's National Institute of Standards and Technology, provides the infrastructure necessary for large-scale evaluation of text retrieval methodologies. With the goal of accelerating research in this area, TREC created the first large test collections of full-text documents and standardized retrieval evaluation. The impact has been significant; since TREC's beginning in 1992, retrieval effectiveness has approximately doubled. TREC has built a variety of large test collections, including collections for such specialized retrieval tasks as cross-language retrieval and retrieval of speech. Moreover, TREC has accelerated the transfer of research ideas into commercial systems, as demonstrated in the number of retrieval techniques developed in TREC that are now used in Web search engines. This book provides a comprehensive review of TREC research, summarizing the variety of TREC results, documenting the best practices in experimental information retrieval, and suggesting areas for further research. The first part of the book describes TREC's history, test collections, and retrieval methodology. Next, the book provides "track" reports -- describing the evaluations of specific tasks, including routing and filtering, interactive retrieval, and retrieving noisy text. The final part of the book offers perspectives on TREC from such participants as Microsoft Research, University of Massachusetts, Cornell University, University of Waterloo, City University of New York, and IBM. The book will be of interest to researchers in information retrieval and related technologies, including natural language processing.

Content

Enthält die Beiträge: 1. The Text REtrieval Conference - Ellen M. Voorhees and Donna K. Harman 2. The TREC Test Collections - Donna K. Harman 3. Retrieval System Evaluation - Chris Buckley and Ellen M. Voorhees 4. The TREC Ad Hoc Experiments - Donna K. Harman 5. Routing and Filtering - Stephen Robertson and Jamie Callan 6. The TREC Interactive Tracks: Putting the User into Search - Susan T. Dumais and Nicholas J. Belkin 7. Beyond English - Donna K. Harman 8. Retrieving Noisy Text - Ellen M. Voorhees and John S. Garofolo 9.The Very Large Collection and Web Tracks - David Hawking and Nick Craswell 10. Question Answering in TREC - Ellen M. Voorhees 11. The University of Massachusetts and a Dozen TRECs - James Allan, W. Bruce Croft and Jamie Callan 12. How Okapi Came to TREC - Stephen Robertson 13. The SMART Project at TREC - Chris Buckley 14. Ten Years of Ad Hoc Retrieval at TREC Using PIRCS - Kui-Lam Kwok 15. MultiText Experiments for TREC - Gordon V. Cormack, Charles L. A. Clarke, Christopher R. Palmer and Thomas R. Lynam 16. A Language-Modeling Approach to TREC - Djoerd Hiemstra and Wessel Kraaij 17. BM Research Activities at TREC - Eric W. Brown, David Carmel, Martin Franz, Abraham Ittycheriah, Tapas Kanungo, Yoelle Maarek, J. Scott McCarley, Robert L. Mack, John M. Prager, John R. Smith, Aya Soffer, Jason Y. Zien and Alan D. Marwick Epilogue: Metareflections on TREC - Karen Sparck Jones