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  • × theme_ss:"Social tagging"
  • × type_ss:"a"
  1. Voß, J.: Vom Social Tagging zum Semantic Tagging (2008) 0.02 
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    Abstract
    Social Tagging als freie Verschlagwortung durch Nutzer im Web wird immer häufiger mit der Idee des Semantic Web in Zusammenhang gebracht. Wie beide Konzepte in der Praxis konkret zusammenkommen sollen, bleibt jedoch meist unklar. Dieser Artikel soll hier Aufklärung leisten, indem die Kombination von Social Tagging und Semantic Web in Form von Semantic Tagging mit dem Simple Knowledge Organisation System dargestellt und auf die konkreten Möglichkeiten, Vorteile und offenen Fragen der Semantischen Indexierung eingegangen wird.
    Type
    a
  2. Blank, M.; Bopp, T.; Hampel, T.; Schulte, J.: Social Tagging = Soziale Suche? (2008) 0.02 
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    Abstract
    Der effiziente Zugang zu Informationen und Wissen spielt in allen Bereichen unserer heutigen Informationsgesellschaft eine Schlüsselrolle. Aufgrund der immer stärker zunehmenden digitalen Informationsflut ist es schwieriger denn je, aus all den zur Verfügung stehenden Ressourcen gerade die interessanten und benötigten Quellen herauszufiltern. Aus diesem Grund gehört eine Suchfunktion zur Grund( raussetzung von Informationssystemen verschiedenster Art. Dieser Artikel he schreibt die Einbettung von Social Tagging in kooperative Informationssysteme und zeigt verschiedene Synergieeffekte auf, die bei der Verzahnung einer klassi schen Suche im Zusammenspiel mit Tagging entstehen.
    Type
    a
  3. Tschetschonig, K.; Ladengruber, R.; Hampel, T.; Schulte, J.: Kollaborative Tagging-Systeme im Electronic Commerce (2008) 0.02 
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    Abstract
    Social-Tagging-Systeme bieten eine Vielzahl an Vorteilen gegenüber traditionellen und zurzeit eingesetzten Systemen und werden besonders in nicht-kommerziellen Web-2.0-Anwendungen erfolgreich verwendet. Diese Arbeit beschäftigt sich mit den Vor- und Nachteilen von Social Tagging für kollaborative Systeme des Electronic Commerce und stellt einige Beispiele aus der Praxis vor. Es gibt nur wenige Anwendungen aus dem Bereich des Electronic Commerce, die Social Tagging erfolgreich als kritischen Teil ihrer Systeme einsetzen. Deshalb wird das Potenzial von Tagging-Systemen beleuchtet, um eine fundierte Basis für neue Entwicklungen im Geschäftsbereich zu schaffen.
    Type
    a
  4. Peters, I.: Folksonomies & Social Tagging (2023) 0.02 
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    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.
    Type
    a
  5. Derntl, M.; Hampel, T.; Motschnig, R.; Pitner, T.: Social Tagging und Inclusive Universal Access (2008) 0.02 
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    Abstract
    Der vorliegende Artikel beleuchtet und bewertet Social Tagging als aktuelles Phänomen des Web 2.0 im Kontext bekannter Techniken der semantischen Datenorganisation. Tagging wird in einen Raum verwandter Ordnungs- und Strukturierungsansätze eingeordnet, um die fundamentalen Grundlagen des Social Tagging zu identifizieren und zuzuweisen. Dabei wird Tagging anhand des Inclusive Universal Access Paradigmas bewertet, das technische als auch menschlich-soziale Kriterien für die inklusive und barrierefreie Bereitstellung und Nutzung von Diensten definiert. Anhand dieser Bewertung werden fundamentale Prinzipien des "Inclusive Social Tagging" hergeleitet, die der Charakterisierung und Bewertung gängiger Tagging-Funktionalitäten in verbreiteten Web-2.0-Diensten dienen. Aus der Bewertung werden insbesondere Entwicklungsmöglichkeiten von Social Tagging und unterstützenden Diensten erkennbar.
    Type
    a
  6. Schillerwein, S.: ¬Der 'Business Case' für die Nutzung von Social Tagging in Intranets und internen Informationssystemen (2008) 0.02 
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    Abstract
    Trendthemen, wie Social Tagging oder Web 2.0, bergen generell die Gefahr, dass Adaptionsentscheidungen auf Basis von im öffentlichen Internet vorgefundenen und den Medien lautstark thematisierten Erfolgsbeispielen getroffen werden. Für die interne Anwendung in einer Organisation ist dieses Vorgehen jedoch risikoreich. Deshalb sollte ein ausführlicher Business Case am Anfang jedes SocialTagging-Projekts stehen, der Nutzen- und Risikopotenziale realistisch einzuschätzen vermag. Der vorliegende Beitrag listet dazu exemplarisch die wichtigsten Aspekte für die Einschätzung des Wertbeitrags und der Stolpersteine für Social Tagging in Intranets und vergleichbaren internen Informationssystemen wie Mitarbeiterportalen, Dokumenten-Repositories und Knowledge Bases auf.
    Type
    a
  7. Ding, Y.; Jacob, E.K.; Zhang, Z.; Foo, S.; Yan, E.; George, N.L.; Guo, L.: Perspectives on social tagging (2009) 0.02 
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    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.
    Type
    a
  8. Lewen, H.: Personalisierte Ordnung von Objekten basierend auf Vertrauensnetzwerken (2008) 0.02 
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  9. Seehaus, S.: Können Suchmaschinen von Sozialer Software profitieren? (2008) 0.02 
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  10. Schiefner, M.: Social Tagging in der universitären Lehre (2008) 0.01 
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    Abstract
    "Social Tagging" bezeichnet das gemeinsame Verwalten und Verschlagworten von Ressourcen und wird vor allem durch Dienste wie del.icio.us oder bibsonomy immer beliebter. Auch in Blogs wird mittlerweile getaggt. Der folgende Beitrag soll die Frage klären: Können Prozesse wie "wisdom of the crowd" und die Folksonomy mit strukturiert und hierarchisch arbeitenden Hochschulen in Verbindung gebracht werden? Obwohl Tagging im Kern verschiedene Dienste und Aufgaben an Hochschulen betrifft, bleibt die Frage bislang unbeantwortet, ob und wie dies an Hochschulen, vor allem im Prozess des Lehrens und Lernens integriert und nutzbar gemacht werden kann.
    Type
    a
  11. Peters, I.; Schumann, L.; Terliesner, J.: Folksonomy-basiertes Information Retrieval unter der Lupe (2012) 0.01 
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    Abstract
    Social Tagging ist eine weitverbreitete Methode, um nutzergenerierte Inhalte in Webdiensten zu indexieren. Dieser Artikel fasst die aktuelle Forschung zu Folksonomies und Effektivität von Tags in Retrievalsystemen zusammen. Es wurde ein TREC-ähnlicher Retrievaltest mit Tags und Ressourcen aus dem Social Bookmarking-Dienst delicious durchgeführt, welcher in Recall- und Precisionwerten für ausschließlich Tag-basierte Suchen resultierte. Außerdem wurden Tags in verschiedenen Stufen bereinigt und auf ihre Retrieval-Effektivität getestet. Testergebnisse zeigen, dass Retrieval in Folksonomies am besten mit kurzen Anfragen funktioniert. Hierbei sind die Recallwerte hoch, die Precisionwerte jedoch eher niedrig. Die Suchfunktion "power tags only" liefert verbesserte Precisionwerte.
    Type
    a
  12. Lin, N.; Li, D.; Ding, Y.; He, B.; Qin, Z.; Tang, J.; Li, J.; Dong, T.: ¬The dynamic features of Delicious, Flickr, and YouTube (2012) 0.01 
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    Abstract
    This article investigates the dynamic features of social tagging vocabularies in Delicious, Flickr, and YouTube from 2003 to 2008. Three algorithms are designed to study the macro- and micro-tag growth as well as the dynamics of taggers' activities, respectively. Moreover, we propose a Tagger Tag Resource Latent Dirichlet Allocation (TTR-LDA) model to explore the evolution of topics emerging from those social vocabularies. Our results show that (a) at the macro level, tag growth in all the three tagging systems obeys power law distribution with exponents lower than 1; at the micro level, the tag growth of popular resources in all three tagging systems follows a similar power law distribution; (b) the exponents of tag growth vary in different evolving stages of resources; (c) the growth of number of taggers associated with different popular resources presents a feature of convergence over time; (d) the active level of taggers has a positive correlation with the macro-tag growth of different tagging systems; and (e) some topics evolve into several subtopics over time while others experience relatively stable stages in which their contents do not change much, and certain groups of taggers continue their interests in them.
    Type
    a
  13. BOND: Katalogisate-Pool BCS kommt gut an (2008) 0.01 
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    Abstract
    »Die rasante Entwicklung des BOND Community System (BCS) übertrifft unsere Erwartungen«, erklärt Andreas Serr, Produktmanager der BOND-Tochter BOND Library Service GmbH &Co. KG (BLS). Bereits über 10.000 neue Datensätze wurden in den letzten Monaten von BOND-Kunden für BOND-Kunden in den gemeinsamen Datenpool erfasst. Tendenz schnell steigend. Der komplette Katalogisate-Pool, der den Nutzern kostenlos zur Verfügung steht, umfasst inzwischen fast 700.000 Katalogisate. »Das Schöne an BCS ist, dass alle davon profitieren«, unterstreicht Serr. Den Teilnehmern entstehen weder Kosten noch Mehrarbeit. Die Datenübernahme erfolgt bequem per Mausklick aus dem Daten-Pool direkt in den eigenen Katalog. Fast noch einfacher ist es, Daten in BCS zur Verfügung zu stellen. Man erfasst sein Katalogisat wie immer. Mit dem Klick zum Abspeichern landen die Daten automatisch im BCS-Pool. »Damit macht man mit seiner täglichen Arbeit viele andere Bibliotheken glücklich«, ergänzt Serr. Dank der großen Zahl und der Kooperationsbereitschaft der BOND-Anwender funktioniert das System jetzt schon prächtig. »Irgendwie ist die Idee genial und einfach zugleich!« schrieb eine Kundin, die seit Mitte März am BCS teilnimmt. Wie wird man BCS Teilnehmer? Am BCS teilnehmen können alle Anwender von BIBLIOTHECA 2000 (ab Version 2.9) und BIBLIOTHECA.net (Version 2.1). Die Erst-Anmeldung erfolgt per Anmelde-PDF, das unter www.library-service.de/ bcs.htm zum Download bereitsteht. Die Freischaltung erfolgt dann in der Regel innerhalb 24 Stunden.
    Type
    a
  14. Li, D.; Ding, Y.; Sugimoto, C.; He, B.; Tang, J.; Yan, E.; Lin, N.; Qin, Z.; Dong, T.: Modeling topic and community structure in social tagging : the TTR-LDA-Community model (2011) 0.01 
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    Abstract
    The presence of social networks in complex systems has made networks and community structure a focal point of study in many domains. Previous studies have focused on the structural emergence and growth of communities and on the topics displayed within the network. However, few scholars have closely examined the relationship between the thematic and structural properties of networks. Therefore, this article proposes the Tagger Tag Resource-Latent Dirichlet Allocation-Community model (TTR-LDA-Community model), which combines the Latent Dirichlet Allocation (LDA) model with the Girvan-Newman community detection algorithm through an inference mechanism. Using social tagging data from Delicious, this article demonstrates the clustering of active taggers into communities, the topic distributions within communities, and the ranking of taggers, tags, and resources within these communities. The data analysis evaluates patterns in community structure and topical affiliations diachronically. The article evaluates the effectiveness of community detection and the inference mechanism embedded in the model and finds that the TTR-LDA-Community model outperforms other traditional models in tag prediction. This has implications for scholars in domains interested in community detection, profiling, and recommender systems.
    Type
    a
  15. Birkenhake, B.: Semantic Weblog : Erfahrungen vom Bloggen mit Tags und Ontologien (2008) 0.01 
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    Abstract
    Der Begriff "Semantic Weblog" bezeichnet die Idee, zwei Konzepte - nämlich Bloggen und Semantic Web - zusammenzuführen. Ausgangspunkt ist dabei die Tatsache, dass Blogs, die länger bestehen, Wissen über bestimmte Domänen ansammeln. Dieses Wissen wird in einem ersten Schritt durch Volltextanalyse und in einem zweien Schritt durch Kategorie- und Tagging-Mechanismen erschlossen und kann durch weitere Schritte zu einfachen Ontologien ausgebaut werden. Dieser Beitrag gliedert sich in mehrere Teile. Zunächst wird das Konzept und seine ersten Implementierungen sowie mögliche Vernetzung von mehreren Semantic Weblogs vorgestellt. Dann wird ein Einblick in die Erfahrungen aus der Semantic Weblog-Praxis gegeben. Abgeschlossen wird der Artikel durch einen Ausblick.
    Type
    a
  16. Pammer, V.; Ley, T.; Lindstaedt, S.: tagr: Unterstützung in kollaborativen Tagging-Umgebungen durch semantische und assoziative Netzwerke (2008) 0.01 
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    Abstract
    Stellen Sie sich vor, Sie laden ein Bild auf Flickr hoch und bekommen automatisch Vorschläge für Tags sowie Beispiele, wie ähnliche Bilder verschlagwortet worden sind. Wir stellen den Forschungsprototypen tagr vor, der auf Basis von vorhandenen Tags Information über die Benutzerin sowie eine Analyse des Bildes neue Tags für ein Bild vorschlägt. Wir verstehen kollaboratives Tagging als einen Prozess der verteilten Kognition, den wir mit entsprechenden Diensten unterstützen wollen. Wir gehen in diesem Artikel genauer auf den Termähnlichkeitsservice ein, der sich ein semantisches Netzwerk (WordNet) und ein assoziatives Netzwerk (Kookkurrenz der verwendeten Tags) zu Nutze macht. Wir diskutieren die Evaluierung des Prototypen und schließen mit einem Ausblick auf unsere weiteren Arbeiten.
    Type
    a
  17. Heck, T.: Analyse von sozialen Informationen für Autorenempfehlungen (2012) 0.01 
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  18. Catarino, M.E.; Baptista, A.A.: Relating folksonomies with Dublin Core (2008) 0.01 
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    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
    Type
    a
  19. Rolla, P.J.: User tags versus Subject headings : can user-supplied data improve subject access to library collections? (2009) 0.01 
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    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
    Type
    a
  20. Strader, C.R.: Author-assigned keywords versus Library of Congress Subject Headings : implications for the cataloging of electronic theses and dissertations (2009) 0.01 
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    Abstract
    This study is an examination of the overlap between author-assigned keywords and cataloger-assigned Library of Congress Subject Headings (LCSH) for a set of electronic theses and dissertations in Ohio State University's online catalog. The project is intended to contribute to the literature on the issue of keywords versus controlled vocabularies in the use of online catalogs and databases. Findings support previous studies' conclusions that both keywords and controlled vocabularies complement one another. Further, even in the presence of bibliographic record enhancements, such as abstracts or summaries, keywords and subject headings provided a significant number of unique terms that could affect the success of keyword searches. Implications for the maintenance of controlled vocabularies such as LCSH also are discussed in light of the patterns of matches and nonmatches found between the keywords and their corresponding subject headings.
    Date
    10. 9.2000 17:38:22
    Type
    a

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