Search (7 results, page 1 of 1)

0.019374683 = product of:
  0.029062025 = sum of:
    0.0074199745 = weight(_text_:a in 2652) [ClassicSimilarity], result of:
      0.0074199745 = score(doc=2652,freq=10.0), product of:
        0.05209492 = queryWeight, product of:
          1.153047 = idf(docFreq=37942, maxDocs=44218)
          0.045180224 = queryNorm
        0.14243183 = fieldWeight in 2652, product of:
          3.1622777 = tf(freq=10.0), with freq of:
            10.0 = termFreq=10.0
          1.153047 = idf(docFreq=37942, maxDocs=44218)
          0.0390625 = fieldNorm(doc=2652)
    0.021642052 = product of:
      0.043284103 = sum of:
        0.043284103 = weight(_text_:22 in 2652) [ClassicSimilarity], result of:
          0.043284103 = score(doc=2652,freq=4.0), product of:
            0.15821345 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.045180224 = 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)
  0.6666667 = coord(2/3)

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

0.015148811 = product of:
  0.022723217 = sum of:
    0.0074199745 = weight(_text_:a in 2650) [ClassicSimilarity], result of:
      0.0074199745 = score(doc=2650,freq=10.0), product of:
        0.05209492 = queryWeight, product of:
          1.153047 = idf(docFreq=37942, maxDocs=44218)
          0.045180224 = queryNorm
        0.14243183 = fieldWeight in 2650, product of:
          3.1622777 = tf(freq=10.0), with freq of:
            10.0 = termFreq=10.0
          1.153047 = idf(docFreq=37942, maxDocs=44218)
          0.0390625 = fieldNorm(doc=2650)
    0.015303242 = product of:
      0.030606484 = sum of:
        0.030606484 = weight(_text_:22 in 2650) [ClassicSimilarity], result of:
          0.030606484 = score(doc=2650,freq=2.0), product of:
            0.15821345 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.045180224 = 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)
  0.6666667 = coord(2/3)

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

Type

a

0.00869174 = product of:
  0.02607522 = sum of:
    0.02607522 = product of:
      0.05215044 = sum of:
        0.05215044 = weight(_text_:de in 4203) [ClassicSimilarity], result of:
          0.05215044 = score(doc=4203,freq=4.0), product of:
            0.19416152 = queryWeight, product of:
              4.297489 = idf(docFreq=1634, maxDocs=44218)
              0.045180224 = queryNorm
            0.26859307 = fieldWeight in 4203, product of:
              2.0 = tf(freq=4.0), with freq of:
                4.0 = termFreq=4.0
              4.297489 = idf(docFreq=1634, maxDocs=44218)
              0.03125 = fieldNorm(doc=4203)
      0.5 = coord(1/2)
  0.33333334 = coord(1/3)

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".

Imprint

Berlin : de Gruyter, Saur

0.0029264777 = product of:
  0.008779433 = sum of:
    0.008779433 = weight(_text_:a in 1265) [ClassicSimilarity], result of:
      0.008779433 = score(doc=1265,freq=14.0), product of:
        0.05209492 = queryWeight, product of:
          1.153047 = idf(docFreq=37942, maxDocs=44218)
          0.045180224 = queryNorm
        0.1685276 = fieldWeight in 1265, product of:
          3.7416575 = tf(freq=14.0), with freq of:
            14.0 = termFreq=14.0
          1.153047 = idf(docFreq=37942, maxDocs=44218)
          0.0390625 = fieldNorm(doc=1265)
  0.33333334 = coord(1/3)

Abstract

Today I want to talk about categorization, and I want to convince you that a lot of what we think we know about categorization is wrong. In particular, I want to convince you that many of the ways we're attempting to apply categorization to the electronic world are actually a bad fit, because we've adopted habits of mind that are left over from earlier strategies. I also want to convince you that what we're seeing when we see the Web is actually a radical break with previous categorization strategies, rather than an extension of them. The second part of the talk is more speculative, because it is often the case that old systems get broken before people know what's going to take their place. (Anyone watching the music industry can see this at work today.) That's what I think is happening with categorization. What I think is coming instead are much more organic ways of organizing information than our current categorization schemes allow, based on two units -- the link, which can point to anything, and the tag, which is a way of attaching labels to links. The strategy of tagging -- free-form labeling, without regard to categorical constraints -- seems like a recipe for disaster, but as the Web has shown us, you can extract a surprising amount of value from big messy data sets.

Footnote

This piece is based on two talks I gave in the spring of 2005 -- one at the O'Reilly ETech conference in March, entitled "Ontology Is Overrated", and one at the IMCExpo in April entitled "Folksonomies & Tags: The rise of user-developed classification." The written version is a heavily edited concatenation of those two talks.

0.0027093915 = product of:
  0.008128175 = sum of:
    0.008128175 = weight(_text_:a in 1091) [ClassicSimilarity], result of:
      0.008128175 = score(doc=1091,freq=12.0), product of:
        0.05209492 = queryWeight, product of:
          1.153047 = idf(docFreq=37942, maxDocs=44218)
          0.045180224 = queryNorm
        0.15602624 = fieldWeight in 1091, product of:
          3.4641016 = tf(freq=12.0), with freq of:
            12.0 = termFreq=12.0
          1.153047 = idf(docFreq=37942, maxDocs=44218)
          0.0390625 = fieldNorm(doc=1091)
  0.33333334 = coord(1/3)

Abstract

The subject of this article is folksonomies on the Internet. One of the largest folksonomies on the Internet in terms of number of users and tagged websites is the computer program del.icio.us, where more than 100,000 people have tagged the websites that they and others find using their own keywords. How this is done in practice and the patterns to be found are the focus of this article. The empirical basis is the collection of 76,601 different keywords with a total frequency of 178,215 from 500 randomly chosen taggers on del.icio.us at the end of 2005. The keywords collected were then analyzed quantitatively statistically by uncovering their frequency and percentage distribution and through a statistical correspondence analysis in order to uncover possible patterns in the users' tags. Subsequently, a qualitative textual analysis of the tags was made in order to find out by analysis which tagging strategies are represented in the data material. This led to four conclusions. 1) the distribution of keywords follows classic power law; 2) distinct tagging communities are identifiable; 3) the most frequently used tags are situated on a general-specific axis; and 4) nine distinct tagging strategies are observed. These four conclusions are put into perspective collectively in respect of a number of more general and theoretical considerations concerning folksonomies and the classification systems of the future.

Type

a

0.0027093915 = product of:
  0.008128175 = sum of:
    0.008128175 = weight(_text_:a in 2341) [ClassicSimilarity], result of:
      0.008128175 = score(doc=2341,freq=12.0), product of:
        0.05209492 = queryWeight, product of:
          1.153047 = idf(docFreq=37942, maxDocs=44218)
          0.045180224 = queryNorm
        0.15602624 = fieldWeight in 2341, product of:
          3.4641016 = tf(freq=12.0), with freq of:
            12.0 = termFreq=12.0
          1.153047 = idf(docFreq=37942, maxDocs=44218)
          0.0390625 = fieldNorm(doc=2341)
  0.33333334 = coord(1/3)

Abstract

Purpose - This paper aims to discuss and test the claim that user-based tagging allows for access to a wider variety of viewpoints than is found using other forms of online searching. Design/methodology/approach - A general overview of the nature of weblogs and user-based tagging is given, along with other relevant concepts. A case is then analyzed where viewpoints towards a specific issue are searched for using both tag searching (Technorati) and general search engine searching (Google and Google Blog Search). Findings - The claim to greater accessibility through user-based tagging is not overtly supported with these experiments. Further results for both general and tag-specific searching goes against some common assumptions about the types of content found on weblogs as opposed to more general web sites. Research limitations/implications - User-based tagging is still not widespread enough to give conclusive data for analysis. As this changes, further research in this area, using a variety of search subjects, is warranted. Originality/value - Although proponents of user-based tagging attribute many qualities to the practice, these qualities have not been properly documented or demonstrated. This paper partially rectifies this gap by testing one of the claims made, that of accessibility to alternate views, thus adding to the discussion on tagging for both researchers and other interested parties.

Type

a

0.0013273255 = product of:
  0.0039819763 = sum of:
    0.0039819763 = weight(_text_:a in 2897) [ClassicSimilarity], result of:
      0.0039819763 = score(doc=2897,freq=2.0), product of:
        0.05209492 = queryWeight, product of:
          1.153047 = idf(docFreq=37942, maxDocs=44218)
          0.045180224 = queryNorm
        0.07643694 = fieldWeight in 2897, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          1.153047 = idf(docFreq=37942, maxDocs=44218)
          0.046875 = fieldNorm(doc=2897)
  0.33333334 = coord(1/3)

Type

a