Search (76 results, page 1 of 4)

  • × theme_ss:"Social tagging"
  1. Heckner, M.: Tagging, rating, posting : studying forms of user contribution for web-based information management and information retrieval (2009) 0.06
    0.059659507 = product of:
      0.17897852 = sum of:
        0.09633918 = weight(_text_:wide in 2931) [ClassicSimilarity], result of:
          0.09633918 = score(doc=2931,freq=8.0), product of:
            0.19679762 = queryWeight, product of:
              4.4307585 = idf(docFreq=1430, maxDocs=44218)
              0.044416238 = queryNorm
            0.48953426 = fieldWeight in 2931, product of:
              2.828427 = tf(freq=8.0), with freq of:
                8.0 = termFreq=8.0
              4.4307585 = idf(docFreq=1430, maxDocs=44218)
              0.0390625 = fieldNorm(doc=2931)
        0.08263934 = weight(_text_:web in 2931) [ClassicSimilarity], result of:
          0.08263934 = score(doc=2931,freq=20.0), product of:
            0.14495286 = queryWeight, product of:
              3.2635105 = idf(docFreq=4597, maxDocs=44218)
              0.044416238 = queryNorm
            0.5701118 = fieldWeight in 2931, product of:
              4.472136 = tf(freq=20.0), with freq of:
                20.0 = termFreq=20.0
              3.2635105 = idf(docFreq=4597, maxDocs=44218)
              0.0390625 = fieldNorm(doc=2931)
      0.33333334 = coord(2/6)
    
    Content
    The Web of User Contribution - Foundations and Principles of the Social Web - Social Tagging - Rating and Filtering of Digital Resources Empirical Analysisof User Contributions - The Functional and Linguistic Structure of Tags - A Comparative Analysis of Tags for Different Digital Resource Types - Exploring Relevance Assessments in Social IR Systems - Exploring User Contribution Within a Higher Education Scenario - Summary of Empirical Results and Implications for Designing Social Information Systems User Contribution for a Participative Information System - Social Information Architecture for an Online Help System
    Object
    Web 2.0
    RSWK
    World Wide Web 2.0 / Benutzer / Online-Publizieren / Information Retrieval / Soziale Software / Hilfesystem
    Social Tagging / Filter / Web log / World Wide Web 2.0
    Subject
    World Wide Web 2.0 / Benutzer / Online-Publizieren / Information Retrieval / Soziale Software / Hilfesystem
    Social Tagging / Filter / Web log / World Wide Web 2.0
  2. Web-2.0-Dienste als Ergänzung zu algorithmischen Suchmaschinen (2008) 0.05
    0.050622772 = product of:
      0.15186831 = sum of:
        0.0817465 = weight(_text_:wide in 4323) [ClassicSimilarity], result of:
          0.0817465 = score(doc=4323,freq=4.0), product of:
            0.19679762 = queryWeight, product of:
              4.4307585 = idf(docFreq=1430, maxDocs=44218)
              0.044416238 = queryNorm
            0.4153836 = fieldWeight in 4323, product of:
              2.0 = tf(freq=4.0), with freq of:
                4.0 = termFreq=4.0
              4.4307585 = idf(docFreq=1430, maxDocs=44218)
              0.046875 = fieldNorm(doc=4323)
        0.07012181 = weight(_text_:web in 4323) [ClassicSimilarity], result of:
          0.07012181 = score(doc=4323,freq=10.0), product of:
            0.14495286 = queryWeight, product of:
              3.2635105 = idf(docFreq=4597, maxDocs=44218)
              0.044416238 = queryNorm
            0.48375595 = fieldWeight in 4323, product of:
              3.1622777 = tf(freq=10.0), with freq of:
                10.0 = termFreq=10.0
              3.2635105 = idf(docFreq=4597, maxDocs=44218)
              0.046875 = fieldNorm(doc=4323)
      0.33333334 = coord(2/6)
    
    Abstract
    Mit sozialen Suchdiensten - wie z. B. Yahoo Clever, Lycos iQ oder Mister Wong - ist eine Ergänzung und teilweise sogar eine Konkurrenz zu den bisherigen Ansätzen in der Web-Suche entstanden. Während Google und Co. automatisch generierte Trefferlisten bieten, binden soziale Suchdienste die Anwender zu Generierung der Suchergebnisse in den Suchprozess ein. Vor diesem Hintergrund wird in diesem Buch der Frage nachgegangen, inwieweit soziale Suchdienste mit traditionellen Suchmaschinen konkurrieren oder diese qualitativ ergänzen können. Der vorliegende Band beleuchtet die hier aufgeworfene Fragestellung aus verschiedenen Perspektiven, um auf die Bedeutung von sozialen Suchdiensten zu schließen.
    Issue
    Ergebnisse des Fachprojektes "Einbindung von Frage-Antwort-Diensten in die Web-Suche" am Department Information der Hochschule für Angewandte Wissenschaften Hamburg (WS 2007/2008).
    RSWK
    World Wide Web 2.0 / Suchmaschine
    Subject
    World Wide Web 2.0 / Suchmaschine
  3. Watters, C.; Nizam, N.: Knowledge organization on the Web : the emergent role of social classification (2012) 0.04
    0.04360208 = product of:
      0.13080624 = sum of:
        0.067437425 = weight(_text_:wide in 828) [ClassicSimilarity], result of:
          0.067437425 = score(doc=828,freq=2.0), product of:
            0.19679762 = queryWeight, product of:
              4.4307585 = idf(docFreq=1430, maxDocs=44218)
              0.044416238 = queryNorm
            0.342674 = fieldWeight in 828, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              4.4307585 = idf(docFreq=1430, maxDocs=44218)
              0.0546875 = fieldNorm(doc=828)
        0.063368805 = weight(_text_:web in 828) [ClassicSimilarity], result of:
          0.063368805 = score(doc=828,freq=6.0), product of:
            0.14495286 = queryWeight, product of:
              3.2635105 = idf(docFreq=4597, maxDocs=44218)
              0.044416238 = queryNorm
            0.43716836 = fieldWeight in 828, product of:
              2.4494898 = tf(freq=6.0), with freq of:
                6.0 = termFreq=6.0
              3.2635105 = idf(docFreq=4597, maxDocs=44218)
              0.0546875 = fieldNorm(doc=828)
      0.33333334 = coord(2/6)
    
    Abstract
    There are close to a billion websites on the Internet with approximately 400 million users worldwide [www.internetworldstats.com]. People go to websites for a wide variety of different information tasks, from finding a restaurant to serious research. Many of the difficulties with searching the Web, as it is structured currently, can be attributed to increases to scale. The content of the Web is now so large that we only have a rough estimate of the number of sites and the range of information is extremely diverse, from blogs and photos to research articles and news videos.
  4. Peters, I.: Folksonomies & Social Tagging (2023) 0.04
    0.04360208 = product of:
      0.13080624 = sum of:
        0.067437425 = weight(_text_:wide in 796) [ClassicSimilarity], result of:
          0.067437425 = score(doc=796,freq=2.0), product of:
            0.19679762 = queryWeight, product of:
              4.4307585 = idf(docFreq=1430, maxDocs=44218)
              0.044416238 = queryNorm
            0.342674 = fieldWeight in 796, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              4.4307585 = idf(docFreq=1430, maxDocs=44218)
              0.0546875 = fieldNorm(doc=796)
        0.063368805 = weight(_text_:web in 796) [ClassicSimilarity], result of:
          0.063368805 = score(doc=796,freq=6.0), product of:
            0.14495286 = queryWeight, product of:
              3.2635105 = idf(docFreq=4597, maxDocs=44218)
              0.044416238 = queryNorm
            0.43716836 = fieldWeight in 796, product of:
              2.4494898 = tf(freq=6.0), with freq of:
                6.0 = termFreq=6.0
              3.2635105 = idf(docFreq=4597, maxDocs=44218)
              0.0546875 = fieldNorm(doc=796)
      0.33333334 = coord(2/6)
    
    Abstract
    Die Erforschung und der Einsatz von Folksonomies und Social Tagging als nutzerzentrierte Formen der Inhaltserschließung und Wissensrepräsentation haben in den 10 Jahren ab ca. 2005 ihren Höhenpunkt erfahren. Motiviert wurde dies durch die Entwicklung und Verbreitung des Social Web und der wachsenden Nutzung von Social-Media-Plattformen (s. Kapitel E 8 Social Media und Social Web). Beides führte zu einem rasanten Anstieg der im oder über das World Wide Web auffindbaren Menge an potenzieller Information und generierte eine große Nachfrage nach skalierbaren Methoden der Inhaltserschließung.
  5. Ding, Y.; Jacob, E.K.; Zhang, Z.; Foo, S.; Yan, E.; George, N.L.; Guo, L.: Perspectives on social tagging (2009) 0.04
    0.04017412 = product of:
      0.12052235 = sum of:
        0.057803504 = weight(_text_:wide in 3290) [ClassicSimilarity], result of:
          0.057803504 = score(doc=3290,freq=2.0), product of:
            0.19679762 = queryWeight, product of:
              4.4307585 = idf(docFreq=1430, maxDocs=44218)
              0.044416238 = queryNorm
            0.29372054 = fieldWeight in 3290, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              4.4307585 = idf(docFreq=1430, maxDocs=44218)
              0.046875 = fieldNorm(doc=3290)
        0.062718846 = weight(_text_:web in 3290) [ClassicSimilarity], result of:
          0.062718846 = score(doc=3290,freq=8.0), product of:
            0.14495286 = queryWeight, product of:
              3.2635105 = idf(docFreq=4597, maxDocs=44218)
              0.044416238 = queryNorm
            0.43268442 = fieldWeight in 3290, product of:
              2.828427 = tf(freq=8.0), with freq of:
                8.0 = termFreq=8.0
              3.2635105 = idf(docFreq=4597, maxDocs=44218)
              0.046875 = fieldNorm(doc=3290)
      0.33333334 = coord(2/6)
    
    Abstract
    Social tagging is one of the major phenomena transforming the World Wide Web from a static platform into an actively shared information space. This paper addresses various aspects of social tagging, including different views on the nature of social tagging, how to make use of social tags, and how to bridge social tagging with other Web functionalities; it discusses the use of facets to facilitate browsing and searching of tagging data; and it presents an analogy between bibliometrics and tagometrics, arguing that established bibliometric methodologies can be applied to analyze tagging behavior on the Web. Based on the Upper Tag Ontology (UTO), a Web crawler was built to harvest tag data from Delicious, Flickr, and YouTube in September 2007. In total, 1.8 million objects, including bookmarks, photos, and videos, 3.1 million taggers, and 12.1 million tags were collected and analyzed. Some tagging patterns and variations are identified and discussed.
  6. Carlin, S.A.: Schlagwortvergabe durch Nutzende (Tagging) als Hilfsmittel zur Suche im Web : Ansatz, Modelle, Realisierungen (2006) 0.04
    0.03553481 = product of:
      0.10660443 = sum of:
        0.04816959 = weight(_text_:wide in 2476) [ClassicSimilarity], result of:
          0.04816959 = score(doc=2476,freq=2.0), product of:
            0.19679762 = queryWeight, product of:
              4.4307585 = idf(docFreq=1430, maxDocs=44218)
              0.044416238 = queryNorm
            0.24476713 = fieldWeight in 2476, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              4.4307585 = idf(docFreq=1430, maxDocs=44218)
              0.0390625 = fieldNorm(doc=2476)
        0.05843484 = weight(_text_:web in 2476) [ClassicSimilarity], result of:
          0.05843484 = score(doc=2476,freq=10.0), product of:
            0.14495286 = queryWeight, product of:
              3.2635105 = idf(docFreq=4597, maxDocs=44218)
              0.044416238 = queryNorm
            0.40312994 = fieldWeight in 2476, product of:
              3.1622777 = tf(freq=10.0), with freq of:
                10.0 = termFreq=10.0
              3.2635105 = idf(docFreq=4597, maxDocs=44218)
              0.0390625 = fieldNorm(doc=2476)
      0.33333334 = coord(2/6)
    
    Abstract
    Nach dem zu Beginn der Ära des World Wide Web von Hand gepflegte Linklisten und -Verzeichnisse und an Freunde und Kollegen per E-Mail verschickte Links genügten, um die Informationen zu finden, nach denen man suchte, waren schon bald Volltextsuchmaschinen und halbautomatisch betriebene Kataloge notwendig, um den mehr und mehr anschwellenden Informationsfluten des Web Herr zu werden. Heute bereits sind diese Dämme gebrochen und viele Millionen Websites halten Billionen an Einzelseiten mit Informationen vor, von Datenbanken und anderweitig versteckten Informationen ganz zu schweigen. Mit Volltextsuchmaschinen erreicht man bei dieser Masse keine befriedigenden Ergebnisse mehr. Entweder man erzeugt lange Suchterme mit vielen Ausschließungen und ebenso vielen nicht-exklusiven ODER-Verknüpfungen um verschiedene Schreibweisen für den gleichen Term abzudecken oder man wählt von vornherein die Daten-Quelle, an die man seine Fragen stellt, genau aus. Doch oft bleiben nur klassische Web-Suchmaschinen übrig, zumal wenn der Fragende kein Informationsspezialist mit Kenntnissen von Spezialdatenbanken ist, sondern, von dieser Warte aus gesehenen, ein Laie. Und nicht nur im Web selbst, auch in unternehmensinternen Intranets steht man vor diesem Problem. Tausende von indizierten Dokumente mögen ein Eckdatum sein, nach dem sich der Erfolg der Einführung eines Intranets bemessen lässt, aber eine Aussage über die Nützlichkeit ist damit nicht getroffen. Und die bleibt meist hinter den Erwartungen zurück, vor allem bei denen Mitarbeitern, die tatsächlich mit dem Intranet arbeiten müssen. Entscheidend ist für die Informationsauffindung in Inter- und Intranet eine einfach zu nutzende und leicht anpassbare Möglichkeit, neue interessante Inhalte zu entdecken. Mit Tags steht eine mögliche Lösung bereit.
  7. Peters, I.: Folksonomies : indexing and retrieval in Web 2.0 (2009) 0.04
    0.0352358 = product of:
      0.10570739 = sum of:
        0.05449767 = weight(_text_:wide in 4203) [ClassicSimilarity], result of:
          0.05449767 = score(doc=4203,freq=4.0), product of:
            0.19679762 = queryWeight, product of:
              4.4307585 = idf(docFreq=1430, maxDocs=44218)
              0.044416238 = queryNorm
            0.2769224 = fieldWeight in 4203, product of:
              2.0 = tf(freq=4.0), with freq of:
                4.0 = termFreq=4.0
              4.4307585 = idf(docFreq=1430, maxDocs=44218)
              0.03125 = fieldNorm(doc=4203)
        0.051209725 = weight(_text_:web in 4203) [ClassicSimilarity], result of:
          0.051209725 = score(doc=4203,freq=12.0), product of:
            0.14495286 = queryWeight, product of:
              3.2635105 = idf(docFreq=4597, maxDocs=44218)
              0.044416238 = queryNorm
            0.35328537 = fieldWeight in 4203, product of:
              3.4641016 = tf(freq=12.0), with freq of:
                12.0 = termFreq=12.0
              3.2635105 = idf(docFreq=4597, maxDocs=44218)
              0.03125 = fieldNorm(doc=4203)
      0.33333334 = coord(2/6)
    
    Abstract
    Kollaborative Informationsdienste im Web 2.0 werden von den Internetnutzern nicht nur dazu genutzt, digitale Informationsressourcen zu produzieren, sondern auch, um sie inhaltlich mit eigenen Schlagworten, sog. Tags, zu erschließen. Dabei müssen die Nutzer nicht wie bei Bibliothekskatalogen auf Regeln achten. Die Menge an nutzergenerierten Tags innerhalb eines Kollaborativen Informationsdienstes wird als Folksonomy bezeichnet. Die Folksonomies dienen den Nutzern zum Wiederauffinden eigener Ressourcen und für die Recherche nach fremden Ressourcen. Das Buch beschäftigt sich mit Kollaborativen Informationsdiensten, Folksonomies als Methode der Wissensrepräsentation und als Werkzeug des Information Retrievals.
    Footnote
    Zugl.: Düsseldorf, Univ., Diss., 2009 u.d.T.: Peters, Isabella: Folksonomies in Wissensrepräsentation und Information Retrieval Rez. in: IWP - Information Wissenschaft & Praxis, 61(2010) Heft 8, S.469-470 (U. Spree): "... Nachdem sich die Rezensentin durch 418 Seiten Text hindurch gelesen hat, bleibt sie unentschieden, wie der auffällige Einsatz langer Zitate (im Durchschnitt drei Zitate, die länger als vier kleingedruckte Zeilen sind, pro Seite) zu bewerten ist, zumal die Zitate nicht selten rein illustrativen Charakter haben bzw. Isabella Peters noch einmal zitiert, was sie bereits in eigenen Worten ausgedrückt hat. Redundanz und Verlängerung der Lesezeit halten sich hier die Waage mit der Möglichkeit, dass sich die Leserin einen unmittelbaren Eindruck von Sprache und Duktus der zitierten Literatur verschaffen kann. Eindeutig unschön ist das Beenden eines Gedankens oder einer Argumentation durch ein Zitat (z. B. S. 170). Im deutschen Original entstehen auf diese Weise die für deutsche wissenschaftliche Qualifikationsarbeiten typischen denglischen Texte. Für alle, die sich für Wissensrepräsentation, Information Retrieval und kollaborative Informationsdienste interessieren, ist "Folksonomies : Indexing and Retrieval in Web 2.0" trotz der angeführten kleinen Mängel zur Lektüre und Anschaffung - wegen seines beinahe enzyklopädischen Charakters auch als Nachschlage- oder Referenzwerk geeignet - unbedingt zu empfehlen. Abschließend möchte ich mich in einem Punkt der Produktinfo von de Gruyter uneingeschränkt anschließen: ein "Grundlagenwerk für Folksonomies".
    Object
    Web 2.0
    RSWK
    World Wide Web 2.0
    Subject
    World Wide Web 2.0
  8. Farkas, M.G.: Social software in libraries : building collaboration, communication, and community online (2007) 0.03
    0.033320423 = product of:
      0.099961266 = sum of:
        0.04434892 = weight(_text_:web in 2364) [ClassicSimilarity], result of:
          0.04434892 = score(doc=2364,freq=4.0), product of:
            0.14495286 = queryWeight, product of:
              3.2635105 = idf(docFreq=4597, maxDocs=44218)
              0.044416238 = queryNorm
            0.3059541 = fieldWeight in 2364, product of:
              2.0 = tf(freq=4.0), with freq of:
                4.0 = termFreq=4.0
              3.2635105 = idf(docFreq=4597, maxDocs=44218)
              0.046875 = fieldNorm(doc=2364)
        0.05561234 = weight(_text_:computer in 2364) [ClassicSimilarity], result of:
          0.05561234 = score(doc=2364,freq=4.0), product of:
            0.16231956 = queryWeight, product of:
              3.6545093 = idf(docFreq=3109, maxDocs=44218)
              0.044416238 = queryNorm
            0.34261024 = fieldWeight in 2364, product of:
              2.0 = tf(freq=4.0), with freq of:
                4.0 = termFreq=4.0
              3.6545093 = idf(docFreq=3109, maxDocs=44218)
              0.046875 = fieldNorm(doc=2364)
      0.33333334 = coord(2/6)
    
    LCSH
    Wikis (Computer science)
    RSWK
    Bibliothek / Web log
    Subject
    Bibliothek / Web log
    Wikis (Computer science)
  9. Bentley, C.M.; Labelle, P.R.: ¬A comparison of social tagging designs and user participation (2008) 0.03
    0.029578885 = product of:
      0.05915777 = sum of:
        0.020906283 = weight(_text_:web in 2657) [ClassicSimilarity], result of:
          0.020906283 = score(doc=2657,freq=2.0), product of:
            0.14495286 = queryWeight, product of:
              3.2635105 = idf(docFreq=4597, maxDocs=44218)
              0.044416238 = queryNorm
            0.14422815 = fieldWeight in 2657, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.2635105 = idf(docFreq=4597, maxDocs=44218)
              0.03125 = fieldNorm(doc=2657)
        0.02621591 = weight(_text_:computer in 2657) [ClassicSimilarity], result of:
          0.02621591 = score(doc=2657,freq=2.0), product of:
            0.16231956 = queryWeight, product of:
              3.6545093 = idf(docFreq=3109, maxDocs=44218)
              0.044416238 = queryNorm
            0.16150802 = fieldWeight in 2657, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.6545093 = idf(docFreq=3109, maxDocs=44218)
              0.03125 = fieldNorm(doc=2657)
        0.012035574 = product of:
          0.024071148 = sum of:
            0.024071148 = weight(_text_:22 in 2657) [ClassicSimilarity], result of:
              0.024071148 = score(doc=2657,freq=2.0), product of:
                0.1555381 = queryWeight, product of:
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.044416238 = queryNorm
                0.15476047 = fieldWeight in 2657, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.03125 = fieldNorm(doc=2657)
          0.5 = coord(1/2)
      0.5 = coord(3/6)
    
    Abstract
    Social tagging empowers users to categorize content in a personally meaningful way while harnessing their potential to contribute to a collaborative construction of knowledge (Vander Wal, 2007). In addition, social tagging systems offer innovative filtering mechanisms that facilitate resource discovery and browsing (Mathes, 2004). As a result, social tags may support online communication, informal or intended learning as well as the development of online communities. The purpose of this mixed methods study is to examine how undergraduate students participate in social tagging activities in order to learn about their motivations, behaviours and practices. A better understanding of their knowledge, habits and interactions with such systems will help practitioners and developers identify important factors when designing enhancements. In the first phase of the study, students enrolled at a Canadian university completed 103 questionnaires. Quantitative results focusing on general familiarity with social tagging, frequently used Web 2.0 sites, and the purpose for engaging in social tagging activities were compiled. Eight questionnaire respondents participated in follow-up semi-structured interviews that further explored tagging practices by situating questionnaire responses within concrete experiences using popular websites such as YouTube, Facebook, Del.icio.us, and Flickr. Preliminary results of this study echo findings found in the growing literature concerning social tagging from the fields of computer science (Sen et al., 2006) and information science (Golder & Huberman, 2006; Macgregor & McCulloch, 2006). Generally, two classes of social taggers emerge: those who focus on tagging for individual purposes, and those who view tagging as a way to share or communicate meaning to others. Heavy del.icio.us users, for example, were often focused on simply organizing their own content, and seemed to be conscientiously maintaining their own personally relevant categorizations while, in many cases, placing little importance on the tags of others. Conversely, users tagging items primarily to share content preferred to use specific terms to optimize retrieval and discovery by others. Our findings should inform practitioners of how interaction design can be tailored for different tagging systems applications, and how these findings are positioned within the current debate surrounding social tagging among the resource discovery community. We also hope to direct future research in the field to place a greater importance on exploring the benefits of tagging as a socially-driven endeavour rather than uniquely as a means of managing information.
    Source
    Metadata for semantic and social applications : proceedings of the International Conference on Dublin Core and Metadata Applications, Berlin, 22 - 26 September 2008, DC 2008: Berlin, Germany / ed. by Jane Greenberg and Wolfgang Klas
  10. Hammond, T.; Hannay, T.; Lund, B.; Scott, J.: Social bookmarking tools (I) : a general review (2005) 0.02
    0.02489311 = product of:
      0.07467933 = sum of:
        0.05174041 = weight(_text_:web in 1188) [ClassicSimilarity], result of:
          0.05174041 = score(doc=1188,freq=16.0), product of:
            0.14495286 = queryWeight, product of:
              3.2635105 = idf(docFreq=4597, maxDocs=44218)
              0.044416238 = queryNorm
            0.35694647 = fieldWeight in 1188, product of:
              4.0 = tf(freq=16.0), with freq of:
                16.0 = termFreq=16.0
              3.2635105 = idf(docFreq=4597, maxDocs=44218)
              0.02734375 = fieldNorm(doc=1188)
        0.02293892 = weight(_text_:computer in 1188) [ClassicSimilarity], result of:
          0.02293892 = score(doc=1188,freq=2.0), product of:
            0.16231956 = queryWeight, product of:
              3.6545093 = idf(docFreq=3109, maxDocs=44218)
              0.044416238 = queryNorm
            0.14131951 = fieldWeight in 1188, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.6545093 = idf(docFreq=3109, maxDocs=44218)
              0.02734375 = fieldNorm(doc=1188)
      0.33333334 = coord(2/6)
    
    Abstract
    Because, to paraphrase a pop music lyric from a certain rock and roll band of yesterday, "the Web is old, the Web is new, the Web is all, the Web is you", it seems like we might have to face up to some of these stark realities. With the introduction of new social software applications such as blogs, wikis, newsfeeds, social networks, and bookmarking tools (the subject of this paper), the claim that Shelley Powers makes in a Burningbird blog entry seems apposite: "This is the user's web now, which means it's my web and I can make the rules." Reinvention is revolution - it brings us always back to beginnings. We are here going to remind you of hyperlinks in all their glory, sell you on the idea of bookmarking hyperlinks, point you at other folks who are doing the same, and tell you why this is a good thing. Just as long as those hyperlinks (or let's call them plain old links) are managed, tagged, commented upon, and published onto the Web, they represent a user's own personal library placed on public record, which - when aggregated with other personal libraries - allows for rich, social networking opportunities. Why spill any ink (digital or not) in rewriting what someone else has already written about instead of just pointing at the original story and adding the merest of titles, descriptions and tags for future reference? More importantly, why not make these personal 'link playlists' available to oneself and to others from whatever browser or computer one happens to be using at the time? This paper reviews some current initiatives, as of early 2005, in providing public link management applications on the Web - utilities that are often referred to under the general moniker of 'social bookmarking tools'. There are a couple of things going on here: 1) server-side software aimed specifically at managing links with, crucially, a strong, social networking flavour, and 2) an unabashedly open and unstructured approach to tagging, or user classification, of those links.
  11. Sun, A.; Bhowmick, S.S.; Nguyen, K.T.N.; Bai, G.: Tag-based social image retrieval : an empirical evaluation (2011) 0.02
    0.02476748 = product of:
      0.07430244 = sum of:
        0.04816959 = weight(_text_:wide in 4938) [ClassicSimilarity], result of:
          0.04816959 = score(doc=4938,freq=2.0), product of:
            0.19679762 = queryWeight, product of:
              4.4307585 = idf(docFreq=1430, maxDocs=44218)
              0.044416238 = queryNorm
            0.24476713 = fieldWeight in 4938, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              4.4307585 = idf(docFreq=1430, maxDocs=44218)
              0.0390625 = fieldNorm(doc=4938)
        0.026132854 = weight(_text_:web in 4938) [ClassicSimilarity], result of:
          0.026132854 = score(doc=4938,freq=2.0), product of:
            0.14495286 = queryWeight, product of:
              3.2635105 = idf(docFreq=4597, maxDocs=44218)
              0.044416238 = queryNorm
            0.18028519 = fieldWeight in 4938, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.2635105 = idf(docFreq=4597, maxDocs=44218)
              0.0390625 = fieldNorm(doc=4938)
      0.33333334 = coord(2/6)
    
    Abstract
    Tags associated with social images are valuable information source for superior image search and retrieval experiences. Although various heuristics are valuable to boost tag-based search for images, there is a lack of general framework to study the impact of these heuristics. Specifically, the task of ranking images matching a given tag query based on their associated tags in descending order of relevance has not been well studied. In this article, we take the first step to propose a generic, flexible, and extensible framework for this task and exploit it for a systematic and comprehensive empirical evaluation of various methods for ranking images. To this end, we identified five orthogonal dimensions to quantify the matching score between a tagged image and a tag query. These five dimensions are: (i) tag relatedness to measure the degree of effectiveness of a tag describing the tagged image; (ii) tag discrimination to quantify the degree of discrimination of a tag with respect to the entire tagged image collection; (iii) tag length normalization analogous to document length normalization in web search; (iv) tag-query matching model for the matching score computation between an image tag and a query tag; and (v) query model for tag query rewriting. For each dimension, we identify a few implementations and evaluate their impact on NUS-WIDE dataset, the largest human-annotated dataset consisting of more than 269K tagged images from Flickr. We evaluated 81 single-tag queries and 443 multi-tag queries over 288 search methods and systematically compare their performances using standard metrics including Precision at top-K, Mean Average Precision (MAP), Recall, and Normalized Discounted Cumulative Gain (NDCG).
  12. Danowski, P.: Authority files and Web 2.0 : Wikipedia and the PND. An Example (2007) 0.02
    0.022436727 = product of:
      0.06731018 = sum of:
        0.052265707 = weight(_text_:web in 1291) [ClassicSimilarity], result of:
          0.052265707 = score(doc=1291,freq=8.0), product of:
            0.14495286 = queryWeight, product of:
              3.2635105 = idf(docFreq=4597, maxDocs=44218)
              0.044416238 = queryNorm
            0.36057037 = fieldWeight in 1291, product of:
              2.828427 = tf(freq=8.0), with freq of:
                8.0 = termFreq=8.0
              3.2635105 = idf(docFreq=4597, maxDocs=44218)
              0.0390625 = fieldNorm(doc=1291)
        0.0150444675 = product of:
          0.030088935 = sum of:
            0.030088935 = weight(_text_:22 in 1291) [ClassicSimilarity], result of:
              0.030088935 = score(doc=1291,freq=2.0), product of:
                0.1555381 = queryWeight, product of:
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.044416238 = queryNorm
                0.19345059 = fieldWeight in 1291, 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=1291)
          0.5 = coord(1/2)
      0.33333334 = coord(2/6)
    
    Abstract
    More and more users index everything on their own in the web 2.0. There are services for links, videos, pictures, books, encyclopaedic articles and scientific articles. All these services are library independent. But must that really be? Can't libraries help with their experience and tools to make user indexing better? On the experience of a project from German language Wikipedia together with the German person authority files (Personen Namen Datei - PND) located at German National Library (Deutsche Nationalbibliothek) I would like to show what is possible. How users can and will use the authority files, if we let them. We will take a look how the project worked and what we can learn for future projects. Conclusions - Authority files can have a role in the web 2.0 - there must be an open interface/ service for retrieval - everything that is indexed on the net with authority files can be easy integrated in a federated search - O'Reilly: You have to found ways that your data get more important that more it will be used
    Content
    Vortrag anlässlich des Workshops: "Extending the multilingual capacity of The European Library in the EDL project Stockholm, Swedish National Library, 22-23 November 2007".
    Object
    Web 2.0
  13. Harrer, A.; Lohmann, S.: Potenziale von Tagging als partizipative Methode für Lehrportale und E-Learning-Kurse (2008) 0.02
    0.022313368 = product of:
      0.0669401 = sum of:
        0.04587784 = weight(_text_:computer in 2889) [ClassicSimilarity], result of:
          0.04587784 = score(doc=2889,freq=2.0), product of:
            0.16231956 = queryWeight, product of:
              3.6545093 = idf(docFreq=3109, maxDocs=44218)
              0.044416238 = queryNorm
            0.28263903 = fieldWeight in 2889, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.6545093 = idf(docFreq=3109, maxDocs=44218)
              0.0546875 = fieldNorm(doc=2889)
        0.021062255 = product of:
          0.04212451 = sum of:
            0.04212451 = weight(_text_:22 in 2889) [ClassicSimilarity], result of:
              0.04212451 = score(doc=2889,freq=2.0), product of:
                0.1555381 = queryWeight, product of:
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.044416238 = queryNorm
                0.2708308 = fieldWeight in 2889, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.0546875 = fieldNorm(doc=2889)
          0.5 = coord(1/2)
      0.33333334 = coord(2/6)
    
    Date
    21. 6.2009 12:22:44
    Theme
    Computer Based Training
  14. Catarino, M.E.; Baptista, A.A.: Relating folksonomies with Dublin Core (2008) 0.02
    0.022179842 = product of:
      0.066539526 = sum of:
        0.045263432 = weight(_text_:web in 2652) [ClassicSimilarity], result of:
          0.045263432 = score(doc=2652,freq=6.0), product of:
            0.14495286 = queryWeight, product of:
              3.2635105 = idf(docFreq=4597, maxDocs=44218)
              0.044416238 = queryNorm
            0.3122631 = fieldWeight in 2652, product of:
              2.4494898 = tf(freq=6.0), with freq of:
                6.0 = termFreq=6.0
              3.2635105 = idf(docFreq=4597, maxDocs=44218)
              0.0390625 = fieldNorm(doc=2652)
        0.02127609 = product of:
          0.04255218 = sum of:
            0.04255218 = weight(_text_:22 in 2652) [ClassicSimilarity], result of:
              0.04255218 = score(doc=2652,freq=4.0), product of:
                0.1555381 = queryWeight, product of:
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.044416238 = queryNorm
                0.27358043 = fieldWeight in 2652, product of:
                  2.0 = tf(freq=4.0), with freq of:
                    4.0 = termFreq=4.0
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.0390625 = fieldNorm(doc=2652)
          0.5 = coord(1/2)
      0.33333334 = coord(2/6)
    
    Abstract
    Folksonomy is the result of describing Web resources with tags created by Web users. Although it has become a popular application for the description of resources, in general terms Folksonomies are not being conveniently integrated in metadata. However, if the appropriate metadata elements are identified, then further work may be conducted to automatically assign tags to these elements (RDF properties) and use them in Semantic Web applications. This article presents research carried out to continue the project Kinds of Tags, which intends to identify elements required for metadata originating from folksonomies and to propose an application profile for DC Social Tagging. The work provides information that may be used by software applications to assign tags to metadata elements and, therefore, means for tags to be conveniently gathered by metadata interoperability tools. Despite the unquestionably high value of DC and the significance of the already existing properties in DC Terms, the pilot study show revealed a significant number of tags for which no corresponding properties yet existed. A need for new properties, such as Action, Depth, Rate, and Utility was determined. Those potential new properties will have to be validated in a later stage by the DC Social Tagging Community.
    Pages
    S.14-22
    Source
    Metadata for semantic and social applications : proceedings of the International Conference on Dublin Core and Metadata Applications, Berlin, 22 - 26 September 2008, DC 2008: Berlin, Germany / ed. by Jane Greenberg and Wolfgang Klas
  15. Kruk, S.R.; Kruk, E.; Stankiewicz, K.: Evaluation of semantic and social technologies for digital libraries (2009) 0.02
    0.020800762 = product of:
      0.062402282 = sum of:
        0.04434892 = weight(_text_:web in 3387) [ClassicSimilarity], result of:
          0.04434892 = score(doc=3387,freq=4.0), product of:
            0.14495286 = queryWeight, product of:
              3.2635105 = idf(docFreq=4597, maxDocs=44218)
              0.044416238 = queryNorm
            0.3059541 = fieldWeight in 3387, product of:
              2.0 = tf(freq=4.0), with freq of:
                4.0 = termFreq=4.0
              3.2635105 = idf(docFreq=4597, maxDocs=44218)
              0.046875 = fieldNorm(doc=3387)
        0.01805336 = product of:
          0.03610672 = sum of:
            0.03610672 = weight(_text_:22 in 3387) [ClassicSimilarity], result of:
              0.03610672 = score(doc=3387,freq=2.0), product of:
                0.1555381 = queryWeight, product of:
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.044416238 = queryNorm
                0.23214069 = fieldWeight in 3387, 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=3387)
          0.5 = coord(1/2)
      0.33333334 = coord(2/6)
    
    Abstract
    Libraries are the tools we use to learn and to answer our questions. The quality of our work depends, among others, on the quality of the tools we use. Recent research in digital libraries is focused, on one hand on improving the infrastructure of the digital library management systems (DLMS), and on the other on improving the metadata models used to annotate collections of objects maintained by DLMS. The latter includes, among others, the semantic web and social networking technologies. Recently, the semantic web and social networking technologies are being introduced to the digital libraries domain. The expected outcome is that the overall quality of information discovery in digital libraries can be improved by employing social and semantic technologies. In this chapter we present the results of an evaluation of social and semantic end-user information discovery services for the digital libraries.
    Date
    1. 8.2010 12:35:22
  16. Rolla, P.J.: User tags versus Subject headings : can user-supplied data improve subject access to library collections? (2009) 0.02
    0.016470928 = product of:
      0.049412783 = sum of:
        0.031359423 = weight(_text_:web in 3601) [ClassicSimilarity], result of:
          0.031359423 = score(doc=3601,freq=2.0), product of:
            0.14495286 = queryWeight, product of:
              3.2635105 = idf(docFreq=4597, maxDocs=44218)
              0.044416238 = queryNorm
            0.21634221 = fieldWeight in 3601, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.2635105 = idf(docFreq=4597, maxDocs=44218)
              0.046875 = fieldNorm(doc=3601)
        0.01805336 = product of:
          0.03610672 = sum of:
            0.03610672 = weight(_text_:22 in 3601) [ClassicSimilarity], result of:
              0.03610672 = score(doc=3601,freq=2.0), product of:
                0.1555381 = queryWeight, product of:
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.044416238 = queryNorm
                0.23214069 = fieldWeight in 3601, 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=3601)
          0.5 = coord(1/2)
      0.33333334 = coord(2/6)
    
    Abstract
    Some members of the library community, including the Library of Congress Working Group on the Future of Bibliographic Control, have suggested that libraries should open up their catalogs to allow users to add descriptive tags to the bibliographic data in catalog records. The web site LibraryThing currently permits its members to add such user tags to its records for books and therefore provides a useful resource to contrast with library bibliographic records. A comparison between the LibraryThing tags for a group of books and the library-supplied subject headings for the same books shows that users and catalogers approach these descriptors very differently. Because of these differences, user tags can enhance subject access to library materials, but they cannot entirely replace controlled vocabularies such as the Library of Congress subject headings.
    Date
    10. 9.2000 17:38:22
  17. Weiand, K.; Hartl, A.; Hausmann, S.; Furche, T.; Bry, F.: Keyword-based search over semantic data (2012) 0.02
    0.016296698 = product of:
      0.09778018 = sum of:
        0.09778018 = weight(_text_:web in 432) [ClassicSimilarity], result of:
          0.09778018 = score(doc=432,freq=28.0), product of:
            0.14495286 = queryWeight, product of:
              3.2635105 = idf(docFreq=4597, maxDocs=44218)
              0.044416238 = queryNorm
            0.6745654 = fieldWeight in 432, product of:
              5.2915025 = tf(freq=28.0), with freq of:
                28.0 = termFreq=28.0
              3.2635105 = idf(docFreq=4597, maxDocs=44218)
              0.0390625 = fieldNorm(doc=432)
      0.16666667 = coord(1/6)
    
    Abstract
    For a long while, the creation of Web content required at least basic knowledge of Web technologies, meaning that for many Web users, the Web was de facto a read-only medium. This changed with the arrival of the "social Web," when Web applications started to allow users to publish Web content without technological expertise. Here, content creation is often an inclusive, iterative, and interactive process. Examples of social Web applications include blogs, social networking sites, as well as many specialized applications, for example, for saving and sharing bookmarks and publishing photos. Social semantic Web applications are social Web applications in which knowledge is expressed not only in the form of text and multimedia but also through informal to formal annotations that describe, reflect, and enhance the content. These annotations often take the shape of RDF graphs backed by ontologies, but less formal annotations such as free-form tags or tags from a controlled vocabulary may also be available. Wikis are one example of social Web applications for collecting and sharing knowledge. They allow users to easily create and edit documents, so-called wiki pages, using a Web browser. The pages in a wiki are often heavily interlinked, which makes it easy to find related information and browse the content.
    Source
    Semantic search over the Web. Eds.: R. De Virgilio, et al
    Theme
    Semantic Web
  18. Kim, H.L.; Scerri, S.; Breslin, J.G.; Decker, S.; Kim, H.G.: ¬The state of the art in tag ontologies : a semantic model for tagging and folksonomies (2008) 0.02
    0.015938118 = product of:
      0.047814354 = sum of:
        0.03276989 = weight(_text_:computer in 2650) [ClassicSimilarity], result of:
          0.03276989 = score(doc=2650,freq=2.0), product of:
            0.16231956 = queryWeight, product of:
              3.6545093 = idf(docFreq=3109, maxDocs=44218)
              0.044416238 = queryNorm
            0.20188503 = fieldWeight in 2650, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.6545093 = idf(docFreq=3109, maxDocs=44218)
              0.0390625 = fieldNorm(doc=2650)
        0.0150444675 = product of:
          0.030088935 = sum of:
            0.030088935 = weight(_text_:22 in 2650) [ClassicSimilarity], result of:
              0.030088935 = score(doc=2650,freq=2.0), product of:
                0.1555381 = queryWeight, product of:
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.044416238 = queryNorm
                0.19345059 = fieldWeight in 2650, 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=2650)
          0.5 = coord(1/2)
      0.33333334 = coord(2/6)
    
    Abstract
    There is a growing interest into how we represent and share tagging data in collaborative tagging systems. Conventional tags, meaning freely created tags that are not associated with a structured ontology, are not naturally suited for collaborative processes, due to linguistic and grammatical variations, as well as human typing errors. Additionally, tags reflect personal views of the world by individual users, and are not normalised for synonymy, morphology or any other mapping. Our view is that the conventional approach provides very limited semantic value for collaboration. Moreover, in cases where there is some semantic value, automatically sharing semantics via computer manipulations is extremely problematic. This paper explores these problems by discussing approaches for collaborative tagging activities at a semantic level, and presenting conceptual models for collaborative tagging activities and folksonomies. We present criteria for the comparison of existing tag ontologies and discuss their strengths and weaknesses in relation to these criteria.
    Source
    Metadata for semantic and social applications : proceedings of the International Conference on Dublin Core and Metadata Applications, Berlin, 22 - 26 September 2008, DC 2008: Berlin, Germany / ed. by Jane Greenberg and Wolfgang Klas
  19. Santini, M.: Zero, single, or multi? : genre of web pages through the users' perspective (2008) 0.01
    0.013773223 = product of:
      0.08263934 = sum of:
        0.08263934 = weight(_text_:web in 2059) [ClassicSimilarity], result of:
          0.08263934 = score(doc=2059,freq=20.0), product of:
            0.14495286 = queryWeight, product of:
              3.2635105 = idf(docFreq=4597, maxDocs=44218)
              0.044416238 = queryNorm
            0.5701118 = fieldWeight in 2059, product of:
              4.472136 = tf(freq=20.0), with freq of:
                20.0 = termFreq=20.0
              3.2635105 = idf(docFreq=4597, maxDocs=44218)
              0.0390625 = fieldNorm(doc=2059)
      0.16666667 = coord(1/6)
    
    Abstract
    The goal of the study presented in this article is to investigate to what extent the classification of a web page by a single genre matches the users' perspective. The extent of agreement on a single genre label for a web page can help understand whether there is a need for a different classification scheme that overrides the single-genre labelling. My hypothesis is that a single genre label does not account for the users' perspective. In order to test this hypothesis, I submitted a restricted number of web pages (25 web pages) to a large number of web users (135 subjects) asking them to assign only a single genre label to each of the web pages. Users could choose from a list of 21 genre labels, or select one of the two 'escape' options, i.e. 'Add a label' and 'I don't know'. The rationale was to observe the level of agreement on a single genre label per web page, and draw some conclusions about the appropriateness of limiting the assignment to only a single label when doing genre classification of web pages. Results show that users largely disagree on the label to be assigned to a web page.
  20. Yi, K.: Harnessing collective intelligence in social tagging using Delicious (2012) 0.01
    0.013725774 = product of:
      0.04117732 = sum of:
        0.026132854 = weight(_text_:web in 515) [ClassicSimilarity], result of:
          0.026132854 = score(doc=515,freq=2.0), product of:
            0.14495286 = queryWeight, product of:
              3.2635105 = idf(docFreq=4597, maxDocs=44218)
              0.044416238 = queryNorm
            0.18028519 = fieldWeight in 515, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.2635105 = idf(docFreq=4597, maxDocs=44218)
              0.0390625 = fieldNorm(doc=515)
        0.0150444675 = product of:
          0.030088935 = sum of:
            0.030088935 = weight(_text_:22 in 515) [ClassicSimilarity], result of:
              0.030088935 = score(doc=515,freq=2.0), product of:
                0.1555381 = queryWeight, product of:
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.044416238 = queryNorm
                0.19345059 = fieldWeight in 515, 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=515)
          0.5 = coord(1/2)
      0.33333334 = coord(2/6)
    
    Abstract
    A new collaborative approach in information organization and sharing has recently arisen, known as collaborative tagging or social indexing. A key element of collaborative tagging is the concept of collective intelligence (CI), which is a shared intelligence among all participants. This research investigates the phenomenon of social tagging in the context of CI with the aim to serve as a stepping-stone towards the mining of truly valuable social tags for web resources. This study focuses on assessing and evaluating the degree of CI embedded in social tagging over time in terms of two-parameter values, number of participants, and top frequency ranking window. Five different metrics were adopted and utilized for assessing the similarity between ranking lists: overlapList, overlapRank, Footrule, Fagin's measure, and the Inverse Rank measure. The result of this study demonstrates that a substantial degree of CI is most likely to be achieved when somewhere between the first 200 and 400 people have participated in tagging, and that a target degree of CI can be projected by controlling the two factors along with the selection of a similarity metric. The study also tests some experimental conditions for detecting social tags with high CI degree. The results of this study can be applicable to the study of filtering social tags based on CI; filtered social tags may be utilized for the metadata creation of tagged resources and possibly for the retrieval of tagged resources.
    Date
    25.12.2012 15:22:37

Languages

  • e 53
  • d 22
  • i 1
  • More… Less…

Types

  • a 62
  • el 9
  • m 9
  • s 3
  • b 2
  • x 1
  • More… Less…

Classifications