Search (3 results, page 1 of 1)

  • × classification_ss:"06.74"
  • × language_ss:"e"
  • × year_i:[2010 TO 2020}
  1. Liu, B.: Web data mining : exploring hyperlinks, contents, and usage data (2011) 0.00
    0.0014490295 = product of:
      0.002898059 = sum of:
        0.002898059 = product of:
          0.005796118 = sum of:
            0.005796118 = weight(_text_:a in 354) [ClassicSimilarity], result of:
              0.005796118 = score(doc=354,freq=10.0), product of:
                0.050867476 = queryWeight, product of:
                  1.153047 = idf(docFreq=37942, maxDocs=44218)
                  0.0441157 = queryNorm
                0.11394546 = fieldWeight in 354, product of:
                  3.1622777 = tf(freq=10.0), with freq of:
                    10.0 = termFreq=10.0
                  1.153047 = idf(docFreq=37942, maxDocs=44218)
                  0.03125 = fieldNorm(doc=354)
          0.5 = coord(1/2)
      0.5 = coord(1/2)
    
    Abstract
    Web mining aims to discover useful information and knowledge from the Web hyperlink structure, page contents, and usage data. Although Web mining uses many conventional data mining techniques, it is not purely an application of traditional data mining due to the semistructured and unstructured nature of the Web data and its heterogeneity. It has also developed many of its own algorithms and techniques. Liu has written a comprehensive text on Web data mining. Key topics of structure mining, content mining, and usage mining are covered both in breadth and in depth. His book brings together all the essential concepts and algorithms from related areas such as data mining, machine learning, and text processing to form an authoritative and coherent text. The book offers a rich blend of theory and practice, addressing seminal research ideas, as well as examining the technology from a practical point of view. It is suitable for students, researchers and practitioners interested in Web mining both as a learning text and a reference book. Lecturers can readily use it for classes on data mining, Web mining, and Web search. Additional teaching materials such as lecture slides, datasets, and implemented algorithms are available online.
  2. Peters, C.; Braschler, M.; Clough, P.: Multilingual information retrieval : from research to practice (2012) 0.00
    0.0012960513 = product of:
      0.0025921026 = sum of:
        0.0025921026 = product of:
          0.0051842052 = sum of:
            0.0051842052 = weight(_text_:a in 361) [ClassicSimilarity], result of:
              0.0051842052 = score(doc=361,freq=8.0), product of:
                0.050867476 = queryWeight, product of:
                  1.153047 = idf(docFreq=37942, maxDocs=44218)
                  0.0441157 = queryNorm
                0.10191591 = fieldWeight in 361, product of:
                  2.828427 = tf(freq=8.0), with freq of:
                    8.0 = termFreq=8.0
                  1.153047 = idf(docFreq=37942, maxDocs=44218)
                  0.03125 = fieldNorm(doc=361)
          0.5 = coord(1/2)
      0.5 = coord(1/2)
    
    Abstract
    We are living in a multilingual world and the diversity in languages which are used to interact with information access systems has generated a wide variety of challenges to be addressed by computer and information scientists. The growing amount of non-English information accessible globally and the increased worldwide exposure of enterprises also necessitates the adaptation of Information Retrieval (IR) methods to new, multilingual settings.Peters, Braschler and Clough present a comprehensive description of the technologies involved in designing and developing systems for Multilingual Information Retrieval (MLIR). They provide readers with broad coverage of the various issues involved in creating systems to make accessible digitally stored materials regardless of the language(s) they are written in. Details on Cross-Language Information Retrieval (CLIR) are also covered that help readers to understand how to develop retrieval systems that cross language boundaries. Their work is divided into six chapters and accompanies the reader step-by-step through the various stages involved in building, using and evaluating MLIR systems. The book concludes with some examples of recent applications that utilise MLIR technologies. Some of the techniques described have recently started to appear in commercial search systems, while others have the potential to be part of future incarnations.The book is intended for graduate students, scholars, and practitioners with a basic understanding of classical text retrieval methods. It offers guidelines and information on all aspects that need to be taken into consideration when building MLIR systems, while avoiding too many 'hands-on details' that could rapidly become obsolete. Thus it bridges the gap between the material covered by most of the classical IR textbooks and the novel requirements related to the acquisition and dissemination of information in whatever language it is stored.
  3. Interactive information seeking, behaviour and retrieval (2011) 0.00
    9.164467E-4 = product of:
      0.0018328934 = sum of:
        0.0018328934 = product of:
          0.0036657867 = sum of:
            0.0036657867 = weight(_text_:a in 542) [ClassicSimilarity], result of:
              0.0036657867 = score(doc=542,freq=4.0), product of:
                0.050867476 = queryWeight, product of:
                  1.153047 = idf(docFreq=37942, maxDocs=44218)
                  0.0441157 = queryNorm
                0.072065435 = fieldWeight in 542, product of:
                  2.0 = tf(freq=4.0), with freq of:
                    4.0 = termFreq=4.0
                  1.153047 = idf(docFreq=37942, maxDocs=44218)
                  0.03125 = fieldNorm(doc=542)
          0.5 = coord(1/2)
      0.5 = coord(1/2)
    
    Abstract
    Information retrieval (IR) is a complex human activity supported by sophisticated systems. Information science has contributed much to the design and evaluation of previous generations of IR system development and to our general understanding of how such systems should be designed and yet, due to the increasing success and diversity of IR systems, many recent textbooks concentrate on IR systems themselves and ignore the human side of searching for information. This book is the first text to provide an information science perspective on IR. Unique in its scope, the book covers the whole spectrum of information retrieval, including: history and background information; behaviour and seeking task-based information; searching and retrieval approaches to investigating information; interaction and behaviour information; representation access models; evaluation interfaces for IR; interactive techniques; web retrieval, ranking and personalization; and, recommendation, collaboration and social search multimedia: interfaces and access. A key text for senior undergraduates and masters' level students of all information and library studies courses, this book is also useful for practising LIS professionals who need to better appreciate how IR systems are designed, implemented and evaluated.