Search (3 results, page 1 of 1)

  • × classification_ss:"54.65 / Webentwicklung / Webanwendungen"
  • × language_ss:"e"
  1. Aberer, K. et al.: ¬The Semantic Web : 6th International Semantic Web Conference, 2nd Asian Semantic Web Conference, ISWC 2007 + ASWC 2007, Busan, Korea, November 11-15, 2007 : proceedings (2007) 0.00
    0.0038264496 = product of:
      0.0076528993 = sum of:
        0.0076528993 = product of:
          0.022958698 = sum of:
            0.022958698 = weight(_text_:12 in 2477) [ClassicSimilarity], result of:
              0.022958698 = score(doc=2477,freq=4.0), product of:
                0.13281173 = queryWeight, product of:
                  2.765864 = idf(docFreq=7562, maxDocs=44218)
                  0.048018172 = queryNorm
                0.1728665 = fieldWeight in 2477, product of:
                  2.0 = tf(freq=4.0), with freq of:
                    4.0 = termFreq=4.0
                  2.765864 = idf(docFreq=7562, maxDocs=44218)
                  0.03125 = fieldNorm(doc=2477)
          0.33333334 = coord(1/3)
      0.5 = coord(1/2)
    
    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.
  2. Hearst, M.A.: Search user interfaces (2009) 0.00
    0.0027057086 = product of:
      0.005411417 = sum of:
        0.005411417 = product of:
          0.01623425 = sum of:
            0.01623425 = weight(_text_:12 in 4029) [ClassicSimilarity], result of:
              0.01623425 = score(doc=4029,freq=2.0), product of:
                0.13281173 = queryWeight, product of:
                  2.765864 = idf(docFreq=7562, maxDocs=44218)
                  0.048018172 = queryNorm
                0.12223507 = fieldWeight in 4029, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  2.765864 = idf(docFreq=7562, maxDocs=44218)
                  0.03125 = fieldNorm(doc=4029)
          0.33333334 = coord(1/3)
      0.5 = coord(1/2)
    
    Footnote
    Rez. in: JASIST 63(2012) no.12, S. 2555-2556 (M. Efron)
  3. Langville, A.N.; Meyer, C.D.: Google's PageRank and beyond : the science of search engine rankings (2006) 0.00
    0.0020292813 = product of:
      0.0040585627 = sum of:
        0.0040585627 = product of:
          0.012175688 = sum of:
            0.012175688 = weight(_text_:12 in 6) [ClassicSimilarity], result of:
              0.012175688 = score(doc=6,freq=2.0), product of:
                0.13281173 = queryWeight, product of:
                  2.765864 = idf(docFreq=7562, maxDocs=44218)
                  0.048018172 = queryNorm
                0.0916763 = fieldWeight in 6, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  2.765864 = idf(docFreq=7562, maxDocs=44218)
                  0.0234375 = fieldNorm(doc=6)
          0.33333334 = coord(1/3)
      0.5 = coord(1/2)
    
    Content
    Chapter 9. Accelerating the Computation of PageRank: 9.1 An Adaptive Power Method - 9.2 Extrapolation - 9.3 Aggregation - 9.4 Other Numerical Methods Chapter 10. Updating the PageRank Vector: 10.1 The Two Updating Problems and their History - 10.2 Restarting the Power Method - 10.3 Approximate Updating Using Approximate Aggregation - 10.4 Exact Aggregation - 10.5 Exact vs. Approximate Aggregation - 10.6 Updating with Iterative Aggregation - 10.7 Determining the Partition - 10.8 Conclusions Chapter 11. The HITS Method for Ranking Webpages: 11.1 The HITS Algorithm - 11.2 HITS Implementation - 11.3 HITS Convergence - 11.4 HITS Example - 11.5 Strengths and Weaknesses of HITS - 11.6 HITS's Relationship to Bibliometrics - 11.7 Query-Independent HITS - 11.8 Accelerating HITS - 11.9 HITS Sensitivity Chapter 12. Other Link Methods for Ranking Webpages: 12.1 SALSA - 12.2 Hybrid Ranking Methods - 12.3 Rankings based on Traffic Flow Chapter 13. The Future of Web Information Retrieval: 13.1 Spam - 13.2 Personalization - 13.3 Clustering - 13.4 Intelligent Agents - 13.5 Trends and Time-Sensitive Search - 13.6 Privacy and Censorship - 13.7 Library Classification Schemes - 13.8 Data Fusion Chapter 14. Resources for Web Information Retrieval: 14.1 Resources for Getting Started - 14.2 Resources for Serious Study Chapter 15. The Mathematics Guide: 15.1 Linear Algebra - 15.2 Perron-Frobenius Theory - 15.3 Markov Chains - 15.4 Perron Complementation - 15.5 Stochastic Complementation - 15.6 Censoring - 15.7 Aggregation - 15.8 Disaggregation

Types