Search (1502 results, page 1 of 76)

  • × year_i:[2000 TO 2010}
  1. Hotho, A.; Bloehdorn, S.: Data Mining 2004 : Text classification by boosting weak learners based on terms and concepts (2004) 0.32 
    0.31793308 = sum of:
  0.07470384 = product of:
    0.22411151 = sum of:
      0.22411151 = weight(_text_:3a in 562) [ClassicSimilarity], result of:
        0.22411151 = score(doc=562,freq=2.0), product of:
          0.39876214 = queryWeight, product of:
            8.478011 = idf(docFreq=24, maxDocs=44218)
            0.047034867 = queryNorm
          0.56201804 = fieldWeight in 562, product of:
            1.4142135 = tf(freq=2.0), with freq of:
              2.0 = termFreq=2.0
            8.478011 = idf(docFreq=24, maxDocs=44218)
            0.046875 = fieldNorm(doc=562)
    0.33333334 = coord(1/3)
  0.22411151 = weight(_text_:2f in 562) [ClassicSimilarity], result of:
    0.22411151 = score(doc=562,freq=2.0), product of:
      0.39876214 = queryWeight, product of:
        8.478011 = idf(docFreq=24, maxDocs=44218)
        0.047034867 = queryNorm
      0.56201804 = fieldWeight in 562, product of:
        1.4142135 = tf(freq=2.0), with freq of:
          2.0 = termFreq=2.0
        8.478011 = idf(docFreq=24, maxDocs=44218)
        0.046875 = fieldNorm(doc=562)
  0.019117726 = product of:
    0.038235452 = sum of:
      0.038235452 = weight(_text_:22 in 562) [ClassicSimilarity], result of:
        0.038235452 = score(doc=562,freq=2.0), product of:
          0.1647081 = queryWeight, product of:
            3.5018296 = idf(docFreq=3622, maxDocs=44218)
            0.047034867 = queryNorm
          0.23214069 = fieldWeight in 562, 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=562)
    0.5 = coord(1/2)
    Content
    Vgl.: http://www.google.de/url?sa=t&rct=j&q=&esrc=s&source=web&cd=1&cad=rja&ved=0CEAQFjAA&url=http%3A%2F%2Fciteseerx.ist.psu.edu%2Fviewdoc%2Fdownload%3Fdoi%3D10.1.1.91.4940%26rep%3Drep1%26type%3Dpdf&ei=dOXrUMeIDYHDtQahsIGACg&usg=AFQjCNHFWVh6gNPvnOrOS9R3rkrXCNVD-A&sig2=5I2F5evRfMnsttSgFF9g7Q&bvm=bv.1357316858,d.Yms.
    Date
    8. 1.2013 10:22:32
  2. Schrodt, R.: Tiefen und Untiefen im wissenschaftlichen Sprachgebrauch (2008) 0.27 
    0.26561368 = product of:
  0.3984205 = sum of:
    0.09960513 = product of:
      0.29881537 = sum of:
        0.29881537 = weight(_text_:3a in 140) [ClassicSimilarity], result of:
          0.29881537 = score(doc=140,freq=2.0), product of:
            0.39876214 = queryWeight, product of:
              8.478011 = idf(docFreq=24, maxDocs=44218)
              0.047034867 = queryNorm
            0.7493574 = fieldWeight in 140, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              8.478011 = idf(docFreq=24, maxDocs=44218)
              0.0625 = fieldNorm(doc=140)
      0.33333334 = coord(1/3)
    0.29881537 = weight(_text_:2f in 140) [ClassicSimilarity], result of:
      0.29881537 = score(doc=140,freq=2.0), product of:
        0.39876214 = queryWeight, product of:
          8.478011 = idf(docFreq=24, maxDocs=44218)
          0.047034867 = queryNorm
        0.7493574 = fieldWeight in 140, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          8.478011 = idf(docFreq=24, maxDocs=44218)
          0.0625 = fieldNorm(doc=140)
  0.6666667 = coord(2/3)
    Content
    Vgl. auch: https://studylibde.com/doc/13053640/richard-schrodt. Vgl. auch: http%3A%2F%2Fwww.univie.ac.at%2FGermanistik%2Fschrodt%2Fvorlesung%2Fwissenschaftssprache.doc&usg=AOvVaw1lDLDR6NFf1W0-oC9mEUJf.
  3. Vetere, G.; Lenzerini, M.: Models for semantic interoperability in service-oriented architectures (2005) 0.23 
    0.23241195 = product of:
  0.3486179 = sum of:
    0.08715448 = product of:
      0.26146343 = sum of:
        0.26146343 = weight(_text_:3a in 306) [ClassicSimilarity], result of:
          0.26146343 = score(doc=306,freq=2.0), product of:
            0.39876214 = queryWeight, product of:
              8.478011 = idf(docFreq=24, maxDocs=44218)
              0.047034867 = queryNorm
            0.65568775 = fieldWeight in 306, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              8.478011 = idf(docFreq=24, maxDocs=44218)
              0.0546875 = fieldNorm(doc=306)
      0.33333334 = coord(1/3)
    0.26146343 = weight(_text_:2f in 306) [ClassicSimilarity], result of:
      0.26146343 = score(doc=306,freq=2.0), product of:
        0.39876214 = queryWeight, product of:
          8.478011 = idf(docFreq=24, maxDocs=44218)
          0.047034867 = queryNorm
        0.65568775 = fieldWeight in 306, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          8.478011 = idf(docFreq=24, maxDocs=44218)
          0.0546875 = fieldNorm(doc=306)
  0.6666667 = coord(2/3)
    Content
    Vgl.: http://ieeexplore.ieee.org/xpl/login.jsp?tp=&arnumber=5386707&url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Farnumber%3D5386707.
  4. Mas, S.; Marleau, Y.: Proposition of a faceted classification model to support corporate information organization and digital records management (2009) 0.20 
    0.19921026 = product of:
  0.29881537 = sum of:
    0.07470384 = product of:
      0.22411151 = sum of:
        0.22411151 = weight(_text_:3a in 2918) [ClassicSimilarity], result of:
          0.22411151 = score(doc=2918,freq=2.0), product of:
            0.39876214 = queryWeight, product of:
              8.478011 = idf(docFreq=24, maxDocs=44218)
              0.047034867 = queryNorm
            0.56201804 = fieldWeight in 2918, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              8.478011 = idf(docFreq=24, maxDocs=44218)
              0.046875 = fieldNorm(doc=2918)
      0.33333334 = coord(1/3)
    0.22411151 = weight(_text_:2f in 2918) [ClassicSimilarity], result of:
      0.22411151 = score(doc=2918,freq=2.0), product of:
        0.39876214 = queryWeight, product of:
          8.478011 = idf(docFreq=24, maxDocs=44218)
          0.047034867 = queryNorm
        0.56201804 = fieldWeight in 2918, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          8.478011 = idf(docFreq=24, maxDocs=44218)
          0.046875 = fieldNorm(doc=2918)
  0.6666667 = coord(2/3)
    Footnote
    Vgl.: http://ieeexplore.ieee.org/Xplore/login.jsp?reload=true&url=http%3A%2F%2Fieeexplore.ieee.org%2Fiel5%2F4755313%2F4755314%2F04755480.pdf%3Farnumber%3D4755480&authDecision=-203.
  5. Donsbach, W.: Wahrheit in den Medien : über den Sinn eines methodischen Objektivitätsbegriffes (2001) 0.17 
    0.16600855 = product of:
  0.24901281 = sum of:
    0.062253203 = product of:
      0.1867596 = sum of:
        0.1867596 = weight(_text_:3a in 5895) [ClassicSimilarity], result of:
          0.1867596 = score(doc=5895,freq=2.0), product of:
            0.39876214 = queryWeight, product of:
              8.478011 = idf(docFreq=24, maxDocs=44218)
              0.047034867 = queryNorm
            0.46834838 = fieldWeight in 5895, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              8.478011 = idf(docFreq=24, maxDocs=44218)
              0.0390625 = fieldNorm(doc=5895)
      0.33333334 = coord(1/3)
    0.1867596 = weight(_text_:2f in 5895) [ClassicSimilarity], result of:
      0.1867596 = score(doc=5895,freq=2.0), product of:
        0.39876214 = queryWeight, product of:
          8.478011 = idf(docFreq=24, maxDocs=44218)
          0.047034867 = queryNorm
        0.46834838 = fieldWeight in 5895, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          8.478011 = idf(docFreq=24, maxDocs=44218)
          0.0390625 = fieldNorm(doc=5895)
  0.6666667 = coord(2/3)
    Source
    Politische Meinung. 381(2001) Nr.1, S.65-74 [https%3A%2F%2Fwww.dgfe.de%2Ffileadmin%2FOrdnerRedakteure%2FSektionen%2FSek02_AEW%2FKWF%2FPublikationen_Reihe_1989-2003%2FBand_17%2FBd_17_1994_355-406_A.pdf&usg=AOvVaw2KcbRsHy5UQ9QRIUyuOLNi]
  6. Stojanovic, N.: Ontology-based Information Retrieval : methods and tools for cooperative query answering (2005) 0.13 
    0.13280684 = product of:
  0.19921026 = sum of:
    0.049802564 = product of:
      0.14940768 = sum of:
        0.14940768 = weight(_text_:3a in 701) [ClassicSimilarity], result of:
          0.14940768 = score(doc=701,freq=2.0), product of:
            0.39876214 = queryWeight, product of:
              8.478011 = idf(docFreq=24, maxDocs=44218)
              0.047034867 = 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)
    0.14940768 = weight(_text_:2f in 701) [ClassicSimilarity], result of:
      0.14940768 = score(doc=701,freq=2.0), product of:
        0.39876214 = queryWeight, product of:
          8.478011 = idf(docFreq=24, maxDocs=44218)
          0.047034867 = 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)
  0.6666667 = coord(2/3)
    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.
  7. Hu, D.; Kaza, S.; Chen, H.: Identifying significant facilitators of dark network evolution (2009) 0.05 
    0.053948723 = product of:
  0.16184616 = sum of:
    0.16184616 = sum of:
      0.12998329 = weight(_text_:networks in 2753) [ClassicSimilarity], result of:
        0.12998329 = score(doc=2753,freq=10.0), product of:
          0.22247115 = queryWeight, product of:
            4.72992 = idf(docFreq=1060, maxDocs=44218)
            0.047034867 = queryNorm
          0.5842703 = fieldWeight in 2753, product of:
            3.1622777 = tf(freq=10.0), with freq of:
              10.0 = termFreq=10.0
            4.72992 = idf(docFreq=1060, maxDocs=44218)
            0.0390625 = fieldNorm(doc=2753)
      0.031862877 = weight(_text_:22 in 2753) [ClassicSimilarity], result of:
        0.031862877 = score(doc=2753,freq=2.0), product of:
          0.1647081 = queryWeight, product of:
            3.5018296 = idf(docFreq=3622, maxDocs=44218)
            0.047034867 = queryNorm
          0.19345059 = fieldWeight in 2753, product of:
            1.4142135 = tf(freq=2.0), with freq of:
              2.0 = termFreq=2.0
            3.5018296 = idf(docFreq=3622, maxDocs=44218)
            0.0390625 = fieldNorm(doc=2753)
  0.33333334 = coord(1/3)
    Abstract
    Social networks evolve over time with the addition and removal of nodes and links to survive and thrive in their environments. Previous studies have shown that the link-formation process in such networks is influenced by a set of facilitators. However, there have been few empirical evaluations to determine the important facilitators. In a research partnership with law enforcement agencies, we used dynamic social-network analysis methods to examine several plausible facilitators of co-offending relationships in a large-scale narcotics network consisting of individuals and vehicles. Multivariate Cox regression and a two-proportion z-test on cyclic and focal closures of the network showed that mutual acquaintance and vehicle affiliations were significant facilitators for the network under study. We also found that homophily with respect to age, race, and gender were not good predictors of future link formation in these networks. Moreover, we examined the social causes and policy implications for the significance and insignificance of various facilitators including common jails on future co-offending. These findings provide important insights into the link-formation processes and the resilience of social networks. In addition, they can be used to aid in the prediction of future links. The methods described can also help in understanding the driving forces behind the formation and evolution of social networks facilitated by mobile and Web technologies.
    Date
    22. 3.2009 18:50:30
  8. Shibata, N.; Kajikawa, Y.; Takeda, Y.; Matsushima, K.: Comparative study on methods of detecting research fronts using different types of citation (2009) 0.04 
    0.038023844 = product of:
  0.114071526 = sum of:
    0.114071526 = sum of:
      0.08220865 = weight(_text_:networks in 2743) [ClassicSimilarity], result of:
        0.08220865 = score(doc=2743,freq=4.0), product of:
          0.22247115 = queryWeight, product of:
            4.72992 = idf(docFreq=1060, maxDocs=44218)
            0.047034867 = queryNorm
          0.369525 = fieldWeight in 2743, product of:
            2.0 = tf(freq=4.0), with freq of:
              4.0 = termFreq=4.0
            4.72992 = idf(docFreq=1060, maxDocs=44218)
            0.0390625 = fieldNorm(doc=2743)
      0.031862877 = weight(_text_:22 in 2743) [ClassicSimilarity], result of:
        0.031862877 = score(doc=2743,freq=2.0), product of:
          0.1647081 = queryWeight, product of:
            3.5018296 = idf(docFreq=3622, maxDocs=44218)
            0.047034867 = queryNorm
          0.19345059 = fieldWeight in 2743, product of:
            1.4142135 = tf(freq=2.0), with freq of:
              2.0 = termFreq=2.0
            3.5018296 = idf(docFreq=3622, maxDocs=44218)
            0.0390625 = fieldNorm(doc=2743)
  0.33333334 = coord(1/3)
    Abstract
    In this article, we performed a comparative study to investigate the performance of methods for detecting emerging research fronts. Three types of citation network, co-citation, bibliographic coupling, and direct citation, were tested in three research domains, gallium nitride (GaN), complex network (CNW), and carbon nanotube (CNT). Three types of citation network were constructed for each research domain, and the papers in those domains were divided into clusters to detect the research front. We evaluated the performance of each type of citation network in detecting a research front by using the following measures of papers in the cluster: visibility, measured by normalized cluster size, speed, measured by average publication year, and topological relevance, measured by density. Direct citation, which could detect large and young emerging clusters earlier, shows the best performance in detecting a research front, and co-citation shows the worst. Additionally, in direct citation networks, the clustering coefficient was the largest, which suggests that the content similarity of papers connected by direct citations is the greatest and that direct citation networks have the least risk of missing emerging research domains because core papers are included in the largest component.
    Date
    22. 3.2009 17:52:50
  9. Leydesdorff, L.: Can networks of journal-journal citations be used as indicators of change in the social sciences? (2003) 0.04 
    0.035997268 = product of:
  0.1079918 = sum of:
    0.1079918 = sum of:
      0.06975635 = weight(_text_:networks in 4460) [ClassicSimilarity], result of:
        0.06975635 = score(doc=4460,freq=2.0), product of:
          0.22247115 = queryWeight, product of:
            4.72992 = idf(docFreq=1060, maxDocs=44218)
            0.047034867 = queryNorm
          0.31355235 = fieldWeight in 4460, product of:
            1.4142135 = tf(freq=2.0), with freq of:
              2.0 = termFreq=2.0
            4.72992 = idf(docFreq=1060, maxDocs=44218)
            0.046875 = fieldNorm(doc=4460)
      0.038235452 = weight(_text_:22 in 4460) [ClassicSimilarity], result of:
        0.038235452 = score(doc=4460,freq=2.0), product of:
          0.1647081 = queryWeight, product of:
            3.5018296 = idf(docFreq=3622, maxDocs=44218)
            0.047034867 = queryNorm
          0.23214069 = fieldWeight in 4460, 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=4460)
  0.33333334 = coord(1/3)
    Date
    6.11.2005 19:02:22
  10. Aringhieri, R.; Damiani, E.; De Capitani di Vimercati, S.; Paraboschi, S.; Samarati, P.: Fuzzy techniques for trust and reputation management in anonymous peer-to-peer systems (2006) 0.04 
    0.035997268 = product of:
  0.1079918 = sum of:
    0.1079918 = sum of:
      0.06975635 = weight(_text_:networks in 5279) [ClassicSimilarity], result of:
        0.06975635 = score(doc=5279,freq=2.0), product of:
          0.22247115 = queryWeight, product of:
            4.72992 = idf(docFreq=1060, maxDocs=44218)
            0.047034867 = queryNorm
          0.31355235 = fieldWeight in 5279, product of:
            1.4142135 = tf(freq=2.0), with freq of:
              2.0 = termFreq=2.0
            4.72992 = idf(docFreq=1060, maxDocs=44218)
            0.046875 = fieldNorm(doc=5279)
      0.038235452 = weight(_text_:22 in 5279) [ClassicSimilarity], result of:
        0.038235452 = score(doc=5279,freq=2.0), product of:
          0.1647081 = queryWeight, product of:
            3.5018296 = idf(docFreq=3622, maxDocs=44218)
            0.047034867 = queryNorm
          0.23214069 = fieldWeight in 5279, 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=5279)
  0.33333334 = coord(1/3)
    Abstract
    Peer-to-peer (P2P) applications are rapidly gaining acceptance among users of Internet-based services, especially because of their capability of exchanging resources while preserving the anonymity of both requesters and providers. However, concerns have been raised about the possibility that malicious users can exploit the network to spread tampered-with resources (e.g., malicious programs and viruses). A considerable amount of research has thus focused on the development of trust and reputation models in P2P networks. In this article, we propose to use fuzzy techniques in the design of reputation systems based on collecting and aggregating peers' opinions. Fuzzy techniques are used in the evaluation and synthesis of all the opinions expressed by peers. The behavior of the proposed system is described by comparison with probabilistic approaches.
    Date
    22. 7.2006 17:06:18
  11. Heiner-Freiling, M.: DDC German - the project, the aims, the methods : new ideas for a well-established traditional classification system (2006) 0.04 
    0.035997268 = product of:
  0.1079918 = sum of:
    0.1079918 = sum of:
      0.06975635 = weight(_text_:networks in 5779) [ClassicSimilarity], result of:
        0.06975635 = score(doc=5779,freq=2.0), product of:
          0.22247115 = queryWeight, product of:
            4.72992 = idf(docFreq=1060, maxDocs=44218)
            0.047034867 = queryNorm
          0.31355235 = fieldWeight in 5779, product of:
            1.4142135 = tf(freq=2.0), with freq of:
              2.0 = termFreq=2.0
            4.72992 = idf(docFreq=1060, maxDocs=44218)
            0.046875 = fieldNorm(doc=5779)
      0.038235452 = weight(_text_:22 in 5779) [ClassicSimilarity], result of:
        0.038235452 = score(doc=5779,freq=2.0), product of:
          0.1647081 = queryWeight, product of:
            3.5018296 = idf(docFreq=3622, maxDocs=44218)
            0.047034867 = queryNorm
          0.23214069 = fieldWeight in 5779, 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=5779)
  0.33333334 = coord(1/3)
    Abstract
    The paper will give a short outline of the project DDC German. The project is not limited to a mere translation of DDC 22, but aims at the implementation of Dewey in the library networks of the German-language countries. Use of DDC mainly for retrieval purposes, not for shelving, leads to certain new aspects in classifying with Dewey which are described in detail and presented together with the German web service Melvil. Based an the German experience of cooperation and data exchange in the field of verbal indexing the paper develops some ideas an future Dewey cooperation between European and American libraries.
  12. Su, F.P.; Lai, K.K.; Sharma, R.R.K.; Kuo, T.H.: Patent priority network : linking patent portfolio to strategic goals (2009) 0.04 
    0.035997268 = product of:
  0.1079918 = sum of:
    0.1079918 = sum of:
      0.06975635 = weight(_text_:networks in 3170) [ClassicSimilarity], result of:
        0.06975635 = score(doc=3170,freq=2.0), product of:
          0.22247115 = queryWeight, product of:
            4.72992 = idf(docFreq=1060, maxDocs=44218)
            0.047034867 = queryNorm
          0.31355235 = fieldWeight in 3170, product of:
            1.4142135 = tf(freq=2.0), with freq of:
              2.0 = termFreq=2.0
            4.72992 = idf(docFreq=1060, maxDocs=44218)
            0.046875 = fieldNorm(doc=3170)
      0.038235452 = weight(_text_:22 in 3170) [ClassicSimilarity], result of:
        0.038235452 = score(doc=3170,freq=2.0), product of:
          0.1647081 = queryWeight, product of:
            3.5018296 = idf(docFreq=3622, maxDocs=44218)
            0.047034867 = queryNorm
          0.23214069 = fieldWeight in 3170, 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=3170)
  0.33333334 = coord(1/3)
    Abstract
    When applying for patents, companies should consider performing patent portfolios as a means of integrating their patent strategy to shape their overall business strategy. This is an important issue for any company in pursuit of enhanced operational performance because the whole raison d'être behind the application of patents is the anticipation of achieving maximum competitive advantage. A prerequisite for such a company is a decision analysis model of patent portfolios because this has the added advantage of being readily applicable to the evaluation of the quality of its competitors' portfolios; thus, by understanding both itself and its competitors, a company can attain a superior position. To demonstrate this, we examine patent priority networks (PPNs) formed through patent family members and claimed priority patents, performing a model of patent portfolio analysis and then going on to determine the algorithms. We suggest that information retrieved from this network can provide a useful reference tool for decision-making by company CEOs, CTOs, R&D managers, and intellectual property managers.
    Date
    5.11.2009 20:35:22
  13. Zschunke, P.: "Mehr Informationen als die Stasi je hatte" : Soziale Netzwerke (2008) 0.04 
    0.03500884 = product of:
  0.10502652 = sum of:
    0.10502652 = sum of:
      0.07798997 = weight(_text_:networks in 1308) [ClassicSimilarity], result of:
        0.07798997 = score(doc=1308,freq=10.0), product of:
          0.22247115 = queryWeight, product of:
            4.72992 = idf(docFreq=1060, maxDocs=44218)
            0.047034867 = queryNorm
          0.35056219 = fieldWeight in 1308, product of:
            3.1622777 = tf(freq=10.0), with freq of:
              10.0 = termFreq=10.0
            4.72992 = idf(docFreq=1060, maxDocs=44218)
            0.0234375 = fieldNorm(doc=1308)
      0.02703655 = weight(_text_:22 in 1308) [ClassicSimilarity], result of:
        0.02703655 = score(doc=1308,freq=4.0), product of:
          0.1647081 = queryWeight, product of:
            3.5018296 = idf(docFreq=3622, maxDocs=44218)
            0.047034867 = queryNorm
          0.16414827 = fieldWeight in 1308, product of:
            2.0 = tf(freq=4.0), with freq of:
              4.0 = termFreq=4.0
            3.5018296 = idf(docFreq=3622, maxDocs=44218)
            0.0234375 = fieldNorm(doc=1308)
  0.33333334 = coord(1/3)
    Content
    "Millionen von Internet-Nutzern drängen in soziale Netze wie StudiVZ und Facebook. Diese Online-Plattformen für die Vernetzung von persönlichen Web-Auftritten entwickeln sich zu einer neuen Art von Massenmedium, wie der Digitale-Medien-Experte Hendrik Speck sagt. Völlig offen sei aber bislang die Frage nach der gesellschaftlichen Verantwortung der "Social Networks". "Die haben mehr Informationen, als die Stasi je hatte", sagt der Informatik-Professor der Fachhochschule Kaiserslautern im Gespräch mit der Nachrichtenagentur AP. Bei den drei Plattformen Facebook, MySpace und Xing hat Speck insgesamt 120 persönliche Attribute gezählt, die auf den persönlichen Seiten der Mitglieder angegeben werden können - angefangen bei Alter und Wohnort über Lieblingsfilme und -musik bis hin zu politischer Neigung und sexueller Ausrichtung. "Wir sehen da einen völlig irrationalen Zugang zu den eigenen Daten", kritisiert der Social-Networks-Forscher. Was aber treibt die Internet-Nutzer zu dieser Art von "digitalem Exhibitionismus"? Speck und seine Studenten haben die Kommunikation in den Netzen mit Hilfe von Software-Agenten und "Crawlern" zu erfassen versucht - das sind Programme, die auf die Seiten dieser Communities vordringen und die Inhalte auswerten. "Wir stellen fest, dass da unheimlich viel offen liegt", sagt Speck. Suche nach Anerkennung und Aufmerksamkeit Als wichtige Antriebskraft hat der Wissenschaftler das Motiv ausgemacht, über den stetig wachsenden Kreis von registrierten "Freunden" Anerkennung und Aufmerksamkeit zu erringen. Bei MySpace oder im SchülerVZ kann sich jeder auf eine Weise präsentieren, wie es in den klassischen Medien kaum möglich ist. Und weil die persönlichen Profile mit wenigen Mausklicks schnell erstellt sind, ist die Eintrittsschwelle sehr viel geringer als bei den Netz-Communities der ersten Stunde, etwa der schon 1985 gegründeten virtuellen Gemeinschaft "The WELL".
    Bislang sind es meist Jugendliche und junge Erwachsene bis etwa 35, die die Mehrheit der Community-Mitglieder ausmachen. Es gebe aber Bestrebungen, die Altersgruppe nach oben zu erweitern, sagt Speck. Die soziale Interaktion in den Social Networks kreist nach seinen Erkenntnissen immer wieder um die gleichen Dinge: 1) Unterhaltung - von Musik bis zu Stars und Sternchen 2) die gesellschaftlich geteilte Schadenfreude nach dem Motto "Pleiten, Pech und Pannen" 3) Flirten und sexuelle Beziehungen. Dabei kommen Männer direkter auf den Punkt als Frauen, die dies hinter anderen Interessen verstecken. Auf der anderen Seite stehen die Betreiber der Netze. Diese erzielen mit der Bereitstellung der Plattform zwar bislang meist noch keine Gewinne, haben aber wegen der gigantischen Zuwachsraten das Interesse von Internet- und Medienunternehmen geweckt, die wie Microsoft oder die Verlagsgruppe Holtzbrinck in Social Networks investieren. Der einzelne Nutzer ist 20 bis 22 Dollar wert Da die Technik der Webseiten nicht besonders aufwendig sei, liege der eigentliche Reichtum in den Nutzern und ihren Daten, erklärt Speck. Bei den großen Plattformen in den USA lasse sich aus den getätigten Investitionen für die Social Networks der Wert eines einzelnen Nutzers auf einen Betrag von 20 bis 22 Dollar (14 bis 15 Euro) schätzen. Der Gegenwert, den die Nutzer liefern sollen, wird vor allem in der Werbung gesehen. Neben der klassischen Bannerwerbung auf den eigenen Seiten versuchen die Betreiber der sozialen Netzwerke nach Darstellung Specks, in andere Dienste wie SMS-Werbung oder E-Mail vorzudringen. Um die Werbe-Zielgruppen immer feiner zu erfassen, werde auch untersucht, wer mit welchem Profil mit wem kommuniziere. "Je tiefer die Vernetzung, desto dichter werden die Informationen", erklärt Speck.
  14. Haythornthwaite, C.: Social networks and information transfer (2009) 0.03 
    0.03466221 = product of:
  0.10398663 = sum of:
    0.10398663 = product of:
      0.20797326 = sum of:
        0.20797326 = weight(_text_:networks in 3877) [ClassicSimilarity], result of:
          0.20797326 = score(doc=3877,freq=10.0), product of:
            0.22247115 = queryWeight, product of:
              4.72992 = idf(docFreq=1060, maxDocs=44218)
              0.047034867 = queryNorm
            0.9348325 = fieldWeight in 3877, product of:
              3.1622777 = tf(freq=10.0), with freq of:
                10.0 = termFreq=10.0
              4.72992 = idf(docFreq=1060, maxDocs=44218)
              0.0625 = fieldNorm(doc=3877)
      0.5 = coord(1/2)
  0.33333334 = coord(1/3)
    Abstract
    Information exchange, transfer and flow can often depend on the motivations of individuals who share that information. This in turn depends on the relationships they maintain with others, and the networks of information sharing resulting from their interconnections. This entry describes the attributes of social networks that facilitate or inhibit the exchange of information, how to discover these networks, and how different configurations of networks can constrain or facilitate information transfer.
  15. Kulyukin, V.A.; Settle, A.: Ranked retrieval with semantic networks and vector spaces (2001) 0.03 
    0.031002825 = product of:
  0.09300847 = sum of:
    0.09300847 = product of:
      0.18601695 = sum of:
        0.18601695 = weight(_text_:networks in 6934) [ClassicSimilarity], result of:
          0.18601695 = score(doc=6934,freq=8.0), product of:
            0.22247115 = queryWeight, product of:
              4.72992 = idf(docFreq=1060, maxDocs=44218)
              0.047034867 = queryNorm
            0.8361396 = fieldWeight in 6934, product of:
              2.828427 = tf(freq=8.0), with freq of:
                8.0 = termFreq=8.0
              4.72992 = idf(docFreq=1060, maxDocs=44218)
              0.0625 = fieldNorm(doc=6934)
      0.5 = coord(1/2)
  0.33333334 = coord(1/3)
    Abstract
    The equivalence of semantic networks with spreading activation and vector spaces with dot product is investigated under ranked retrieval. Semantic networks are viewed as networks of concepts organized in terms of abstraction and packaging relations. It is shown that the two models can be effectively constructed from each other. A formal method is suggested to analyze the models in terms of their relative performance in the same universe of objects
  16. Chen, C.: CiteSpace II : detecting and visualizing emerging trends and transient patterns in scientific literature (2006) 0.03 
    0.029997721 = product of:
  0.089993164 = sum of:
    0.089993164 = sum of:
      0.05813029 = weight(_text_:networks in 5272) [ClassicSimilarity], result of:
        0.05813029 = score(doc=5272,freq=2.0), product of:
          0.22247115 = queryWeight, product of:
            4.72992 = idf(docFreq=1060, maxDocs=44218)
            0.047034867 = queryNorm
          0.26129362 = fieldWeight in 5272, product of:
            1.4142135 = tf(freq=2.0), with freq of:
              2.0 = termFreq=2.0
            4.72992 = idf(docFreq=1060, maxDocs=44218)
            0.0390625 = fieldNorm(doc=5272)
      0.031862877 = weight(_text_:22 in 5272) [ClassicSimilarity], result of:
        0.031862877 = score(doc=5272,freq=2.0), product of:
          0.1647081 = queryWeight, product of:
            3.5018296 = idf(docFreq=3622, maxDocs=44218)
            0.047034867 = queryNorm
          0.19345059 = fieldWeight in 5272, product of:
            1.4142135 = tf(freq=2.0), with freq of:
              2.0 = termFreq=2.0
            3.5018296 = idf(docFreq=3622, maxDocs=44218)
            0.0390625 = fieldNorm(doc=5272)
  0.33333334 = coord(1/3)
    Abstract
    This article describes the latest development of a generic approach to detecting and visualizing emerging trends and transient patterns in scientific literature. The work makes substantial theoretical and methodological contributions to progressive knowledge domain visualization. A specialty is conceptualized and visualized as a time-variant duality between two fundamental concepts in information science: research fronts and intellectual bases. A research front is defined as an emergent and transient grouping of concepts and underlying research issues. The intellectual base of a research front is its citation and co-citation footprint in scientific literature - an evolving network of scientific publications cited by research-front concepts. Kleinberg's (2002) burst-detection algorithm is adapted to identify emergent research-front concepts. Freeman's (1979) betweenness centrality metric is used to highlight potential pivotal points of paradigm shift over time. Two complementary visualization views are designed and implemented: cluster views and time-zone views. The contributions of the approach are that (a) the nature of an intellectual base is algorithmically and temporally identified by emergent research-front terms, (b) the value of a co-citation cluster is explicitly interpreted in terms of research-front concepts, and (c) visually prominent and algorithmically detected pivotal points substantially reduce the complexity of a visualized network. The modeling and visualization process is implemented in CiteSpace II, a Java application, and applied to the analysis of two research fields: mass extinction (1981-2004) and terrorism (1990-2003). Prominent trends and pivotal points in visualized networks were verified in collaboration with domain experts, who are the authors of pivotal-point articles. Practical implications of the work are discussed. A number of challenges and opportunities for future studies are identified.
    Date
    22. 7.2006 16:11:05
  17. Zheng, R.; Li, J.; Chen, H.; Huang, Z.: ¬A framework for authorship identification of online messages : writing-style features and classification techniques (2006) 0.03 
    0.029997721 = product of:
  0.089993164 = sum of:
    0.089993164 = sum of:
      0.05813029 = weight(_text_:networks in 5276) [ClassicSimilarity], result of:
        0.05813029 = score(doc=5276,freq=2.0), product of:
          0.22247115 = queryWeight, product of:
            4.72992 = idf(docFreq=1060, maxDocs=44218)
            0.047034867 = queryNorm
          0.26129362 = fieldWeight in 5276, product of:
            1.4142135 = tf(freq=2.0), with freq of:
              2.0 = termFreq=2.0
            4.72992 = idf(docFreq=1060, maxDocs=44218)
            0.0390625 = fieldNorm(doc=5276)
      0.031862877 = weight(_text_:22 in 5276) [ClassicSimilarity], result of:
        0.031862877 = score(doc=5276,freq=2.0), product of:
          0.1647081 = queryWeight, product of:
            3.5018296 = idf(docFreq=3622, maxDocs=44218)
            0.047034867 = queryNorm
          0.19345059 = fieldWeight in 5276, product of:
            1.4142135 = tf(freq=2.0), with freq of:
              2.0 = termFreq=2.0
            3.5018296 = idf(docFreq=3622, maxDocs=44218)
            0.0390625 = fieldNorm(doc=5276)
  0.33333334 = coord(1/3)
    Abstract
    With the rapid proliferation of Internet technologies and applications, misuse of online messages for inappropriate or illegal purposes has become a major concern for society. The anonymous nature of online-message distribution makes identity tracing a critical problem. We developed a framework for authorship identification of online messages to address the identity-tracing problem. In this framework, four types of writing-style features (lexical, syntactic, structural, and content-specific features) are extracted and inductive learning algorithms are used to build feature-based classification models to identify authorship of online messages. To examine this framework, we conducted experiments on English and Chinese online-newsgroup messages. We compared the discriminating power of the four types of features and of three classification techniques: decision trees, backpropagation neural networks, and support vector machines. The experimental results showed that the proposed approach was able to identify authors of online messages with satisfactory accuracy of 70 to 95%. All four types of message features contributed to discriminating authors of online messages. Support vector machines outperformed the other two classification techniques in our experiments. The high performance we achieved for both the English and Chinese datasets showed the potential of this approach in a multiple-language context.
    Date
    22. 7.2006 16:14:37
  18. Münnich, M.: REUSE or rule harmonization : just a project? (2000) 0.03 
    0.029997721 = product of:
  0.089993164 = sum of:
    0.089993164 = sum of:
      0.05813029 = weight(_text_:networks in 192) [ClassicSimilarity], result of:
        0.05813029 = score(doc=192,freq=2.0), product of:
          0.22247115 = queryWeight, product of:
            4.72992 = idf(docFreq=1060, maxDocs=44218)
            0.047034867 = queryNorm
          0.26129362 = fieldWeight in 192, product of:
            1.4142135 = tf(freq=2.0), with freq of:
              2.0 = termFreq=2.0
            4.72992 = idf(docFreq=1060, maxDocs=44218)
            0.0390625 = fieldNorm(doc=192)
      0.031862877 = weight(_text_:22 in 192) [ClassicSimilarity], result of:
        0.031862877 = score(doc=192,freq=2.0), product of:
          0.1647081 = queryWeight, product of:
            3.5018296 = idf(docFreq=3622, maxDocs=44218)
            0.047034867 = queryNorm
          0.19345059 = fieldWeight in 192, product of:
            1.4142135 = tf(freq=2.0), with freq of:
              2.0 = termFreq=2.0
            3.5018296 = idf(docFreq=3622, maxDocs=44218)
            0.0390625 = fieldNorm(doc=192)
  0.33333334 = coord(1/3)
    Abstract
    German academic libraries acquire a large number of books from British and American publishers. The bibliographic records of the Library of Congress and the British National Bibliography are offered in most German library networks. Thus, projects REUSE and REUSE+ were undertaken when there was a demand for harmonization of Germany cataloging rules with AACR2 (Anglo-American Cataloguing Rules). Experts in the United States and Germany systematically analyzed bibliographic data and compared the codes on which the data were based. Major and minor differences in cataloging rules were identified. The REUSE group proposed German participation in international authority files and changes in RAK, the German cataloging rules. In REUSE+ the different types of hierarchical bibliographic structures in USMARC and MAB2 and other German formats were analyzed. The German project group made suggestions concerning both the German formats and the USMARC format. Steps toward rule alignment and harmonization of online requirements were made when the German Cataloging Rules Conference made decisions on resolutions prepared by the Working Groups on Descriptive Cataloging that dealt with titles, encoding of form titles and conference terms, prefixes in names, hierarchies, entries under persons and corporate bodies, and the conceptual basis of RAK2 in the context of harmonization. Although problems remain, German rule makers have made progress toward internationality.
    Date
    10. 9.2000 17:38:22
  19. Reed, G.M.; Sanders, J.W.: ¬The principle of distribution (2008) 0.03 
    0.029997721 = product of:
  0.089993164 = sum of:
    0.089993164 = sum of:
      0.05813029 = weight(_text_:networks in 1868) [ClassicSimilarity], result of:
        0.05813029 = score(doc=1868,freq=2.0), product of:
          0.22247115 = queryWeight, product of:
            4.72992 = idf(docFreq=1060, maxDocs=44218)
            0.047034867 = queryNorm
          0.26129362 = fieldWeight in 1868, product of:
            1.4142135 = tf(freq=2.0), with freq of:
              2.0 = termFreq=2.0
            4.72992 = idf(docFreq=1060, maxDocs=44218)
            0.0390625 = fieldNorm(doc=1868)
      0.031862877 = weight(_text_:22 in 1868) [ClassicSimilarity], result of:
        0.031862877 = score(doc=1868,freq=2.0), product of:
          0.1647081 = queryWeight, product of:
            3.5018296 = idf(docFreq=3622, maxDocs=44218)
            0.047034867 = queryNorm
          0.19345059 = fieldWeight in 1868, product of:
            1.4142135 = tf(freq=2.0), with freq of:
              2.0 = termFreq=2.0
            3.5018296 = idf(docFreq=3622, maxDocs=44218)
            0.0390625 = fieldNorm(doc=1868)
  0.33333334 = coord(1/3)
    Abstract
    This article introduces a normative principle for the behavior of contemporary computing and communication systems and considers some of its consequences. The principle, named the principle of distribution, says that in a distributed multi-agent system, control resides as much as possible with the individuals constituting the system rather than in centralized agents; and when that is unfeasible or becomes inappropriate due to environmental changes, control evolves upwards from the individuals to an appropriate intermediate level rather than being imposed from above. The setting for the work is the dynamically changing global space resulting from ubiquitous communication. Accordingly, the article begins by determining the characteristics of the distributed multi-agent space it spans. It then fleshes out the principle of distribution, with examples from daily life as well as from Computer Science. The case is made for the principle of distribution to work at various levels of abstraction of system behavior: to inform the high-level discussion that ought to precede the more low-level concerns of technology, protocols, and standardization, but also to facilitate those lower levels. Of the more substantial applications given here of the principle of distribution, a technical example concerns the design of secure ad hoc networks of mobile devices, achievable without any form of centralized authentication or identification but in a solely distributed manner. Here, the context is how the principle can be used to provide new and provably secure protocols for genuinely ubiquitous communication. A second, more managerial example concerns the distributed production and management of open-source software, and a third investigates some pertinent questions involving the dynamic restructuring of control in distributed systems, important in times of disaster or malevolence.
    Date
    1. 6.2008 12:22:41
  20. Meho, L.I.; Rogers, Y.: Citation counting, citation ranking, and h-index of human-computer interaction researchers : a comparison of Scopus and Web of Science (2008) 0.03 
    0.029997721 = product of:
  0.089993164 = sum of:
    0.089993164 = sum of:
      0.05813029 = weight(_text_:networks in 2352) [ClassicSimilarity], result of:
        0.05813029 = score(doc=2352,freq=2.0), product of:
          0.22247115 = queryWeight, product of:
            4.72992 = idf(docFreq=1060, maxDocs=44218)
            0.047034867 = queryNorm
          0.26129362 = fieldWeight in 2352, product of:
            1.4142135 = tf(freq=2.0), with freq of:
              2.0 = termFreq=2.0
            4.72992 = idf(docFreq=1060, maxDocs=44218)
            0.0390625 = fieldNorm(doc=2352)
      0.031862877 = weight(_text_:22 in 2352) [ClassicSimilarity], result of:
        0.031862877 = score(doc=2352,freq=2.0), product of:
          0.1647081 = queryWeight, product of:
            3.5018296 = idf(docFreq=3622, maxDocs=44218)
            0.047034867 = queryNorm
          0.19345059 = fieldWeight in 2352, product of:
            1.4142135 = tf(freq=2.0), with freq of:
              2.0 = termFreq=2.0
            3.5018296 = idf(docFreq=3622, maxDocs=44218)
            0.0390625 = fieldNorm(doc=2352)
  0.33333334 = coord(1/3)
    Abstract
    This study examines the differences between Scopus and Web of Science in the citation counting, citation ranking, and h-index of 22 top human-computer interaction (HCI) researchers from EQUATOR - a large British Interdisciplinary Research Collaboration project. Results indicate that Scopus provides significantly more coverage of HCI literature than Web of Science, primarily due to coverage of relevant ACM and IEEE peer-reviewed conference proceedings. No significant differences exist between the two databases if citations in journals only are compared. Although broader coverage of the literature does not significantly alter the relative citation ranking of individual researchers, Scopus helps distinguish between the researchers in a more nuanced fashion than Web of Science in both citation counting and h-index. Scopus also generates significantly different maps of citation networks of individual scholars than those generated by Web of Science. The study also presents a comparison of h-index scores based on Google Scholar with those based on the union of Scopus and Web of Science. The study concludes that Scopus can be used as a sole data source for citation-based research and evaluation in HCI, especially when citations in conference proceedings are sought, and that researchers should manually calculate h scores instead of relying on system calculations.

Authors

Languages

Types

  • a 1250
  • m 178
  • el 75
  • s 65
  • b 26
  • x 15
  • i 8
  • n 3
  • r 1
  • More… Less…

Themes

Subjects

Classifications