Search (2 results, page 1 of 1)

  • × classification_ss:"06.74 / Informationssysteme"
  • × classification_ss:"31.80 / Angewandte Mathematik"
  1. Berry, M.W.; Browne, M.: Understanding search engines : mathematical modeling and text retrieval (2005) 0.03
    0.027304117 = sum of:
      0.017108764 = product of:
        0.06843506 = sum of:
          0.06843506 = weight(_text_:authors in 7) [ClassicSimilarity], result of:
            0.06843506 = score(doc=7,freq=4.0), product of:
              0.24018547 = queryWeight, product of:
                4.558814 = idf(docFreq=1258, maxDocs=44218)
                0.052685954 = queryNorm
              0.28492588 = fieldWeight in 7, product of:
                2.0 = tf(freq=4.0), with freq of:
                  4.0 = termFreq=4.0
                4.558814 = idf(docFreq=1258, maxDocs=44218)
                0.03125 = fieldNorm(doc=7)
        0.25 = coord(1/4)
      0.010195352 = product of:
        0.020390704 = sum of:
          0.020390704 = weight(_text_:m in 7) [ClassicSimilarity], result of:
            0.020390704 = score(doc=7,freq=4.0), product of:
              0.13110629 = queryWeight, product of:
                2.4884486 = idf(docFreq=9980, maxDocs=44218)
                0.052685954 = queryNorm
              0.15552804 = fieldWeight in 7, product of:
                2.0 = tf(freq=4.0), with freq of:
                  4.0 = termFreq=4.0
                2.4884486 = idf(docFreq=9980, maxDocs=44218)
                0.03125 = fieldNorm(doc=7)
        0.5 = coord(1/2)
    
    Abstract
    The second edition of Understanding Search Engines: Mathematical Modeling and Text Retrieval follows the basic premise of the first edition by discussing many of the key design issues for building search engines and emphasizing the important role that applied mathematics can play in improving information retrieval. The authors discuss important data structures, algorithms, and software as well as user-centered issues such as interfaces, manual indexing, and document preparation. Significant changes bring the text up to date on current information retrieval methods: for example the addition of a new chapter on link-structure algorithms used in search engines such as Google. The chapter on user interface has been rewritten to specifically focus on search engine usability. In addition the authors have added new recommendations for further reading and expanded the bibliography, and have updated and streamlined the index to make it more reader friendly.
    Type
    m
  2. Langville, A.N.; Meyer, C.D.: Google's PageRank and beyond : the science of search engine rankings (2006) 0.01
    0.014480194 = sum of:
      0.009073292 = product of:
        0.036293168 = sum of:
          0.036293168 = weight(_text_:authors in 6) [ClassicSimilarity], result of:
            0.036293168 = score(doc=6,freq=2.0), product of:
              0.24018547 = queryWeight, product of:
                4.558814 = idf(docFreq=1258, maxDocs=44218)
                0.052685954 = queryNorm
              0.15110476 = fieldWeight in 6, product of:
                1.4142135 = tf(freq=2.0), with freq of:
                  2.0 = termFreq=2.0
                4.558814 = idf(docFreq=1258, maxDocs=44218)
                0.0234375 = fieldNorm(doc=6)
        0.25 = coord(1/4)
      0.0054069017 = product of:
        0.010813803 = sum of:
          0.010813803 = weight(_text_:m in 6) [ClassicSimilarity], result of:
            0.010813803 = score(doc=6,freq=2.0), product of:
              0.13110629 = queryWeight, product of:
                2.4884486 = idf(docFreq=9980, maxDocs=44218)
                0.052685954 = queryNorm
              0.0824812 = fieldWeight in 6, product of:
                1.4142135 = tf(freq=2.0), with freq of:
                  2.0 = termFreq=2.0
                2.4884486 = idf(docFreq=9980, maxDocs=44218)
                0.0234375 = fieldNorm(doc=6)
        0.5 = coord(1/2)
    
    Abstract
    Why doesn't your home page appear on the first page of search results, even when you query your own name? How do other Web pages always appear at the top? What creates these powerful rankings? And how? The first book ever about the science of Web page rankings, "Google's PageRank and Beyond" supplies the answers to these and other questions and more. The book serves two very different audiences: the curious science reader and the technical computational reader. The chapters build in mathematical sophistication, so that the first five are accessible to the general academic reader. While other chapters are much more mathematical in nature, each one contains something for both audiences. For example, the authors include entertaining asides such as how search engines make money and how the Great Firewall of China influences research. The book includes an extensive background chapter designed to help readers learn more about the mathematics of search engines, and it contains several MATLAB codes and links to sample Web data sets. The philosophy throughout is to encourage readers to experiment with the ideas and algorithms in the text. Any business seriously interested in improving its rankings in the major search engines can benefit from the clear examples, sample code, and list of resources provided. It includes: many illustrative examples and entertaining asides; MATLAB code; accessible and informal style; and complete and self-contained section for mathematics review.
    Type
    m