Search (90 results, page 1 of 5)

0.10755379 = product of:
  0.21510758 = sum of:
    0.21510758 = product of:
      0.43021515 = sum of:
        0.43021515 = weight(_text_:tagging in 2294) [ClassicSimilarity], result of:
          0.43021515 = score(doc=2294,freq=20.0), product of:
            0.2979515 = queryWeight, product of:
              5.9038734 = idf(docFreq=327, maxDocs=44218)
              0.05046712 = queryNorm
            1.44391 = fieldWeight in 2294, product of:
              4.472136 = tf(freq=20.0), with freq of:
                20.0 = termFreq=20.0
              5.9038734 = idf(docFreq=327, maxDocs=44218)
              0.0546875 = fieldNorm(doc=2294)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Abstract

Purpose: Investigate the combination of controlled and folksonomy approaches to support resource discovery in repositories and digital collections. Aim: Investigate whether use of an established controlled vocabulary can help improve social tagging for better resource discovery. Objectives: (1) Investigate indexing aspects when using only social tagging versus when using social tagging with suggestions from a controlled vocabulary; (2) Investigate above in two different contexts: tagging by readers and tagging by authors; (3) Investigate influence of only social tagging versus social tagging with a controlled vocabulary on retrieval. - Vgl.: http://www.ukoln.ac.uk/projects/enhanced-tagging/.

Theme

Social tagging

0.08745811 = product of:
  0.17491622 = sum of:
    0.17491622 = product of:
      0.34983245 = sum of:
        0.34983245 = weight(_text_:tagging in 309) [ClassicSimilarity], result of:
          0.34983245 = score(doc=309,freq=18.0), product of:
            0.2979515 = queryWeight, product of:
              5.9038734 = idf(docFreq=327, maxDocs=44218)
              0.05046712 = queryNorm
            1.1741256 = fieldWeight in 309, product of:
              4.2426405 = tf(freq=18.0), with freq of:
                18.0 = termFreq=18.0
              5.9038734 = idf(docFreq=327, maxDocs=44218)
              0.046875 = fieldNorm(doc=309)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Abstract

This paper describes a survey on how system vendors and libraries handled tagging in OPACs and discovery layers. Tags are user added subject metadata, also called folksonomies. This survey also investigated user behavior when they face the possibility to tag. The findings indicate that legacy/classic systems have no tagging capability. About 47% of the discovery tools provide tagging function. About 49% of the libraries that have a system with tagging capability have turned the tagging function on in their OPACs and discovery tools. Only 40% of the libraries that turned tagging on actually utilized user added subject metadata as access point to collections. Academic library users are less active in tagging than public library users.

Theme

Social tagging

0.07774055 = product of:
  0.1554811 = sum of:
    0.1554811 = product of:
      0.3109622 = sum of:
        0.3109622 = weight(_text_:tagging in 3134) [ClassicSimilarity], result of:
          0.3109622 = score(doc=3134,freq=2.0), product of:
            0.2979515 = queryWeight, product of:
              5.9038734 = idf(docFreq=327, maxDocs=44218)
              0.05046712 = queryNorm
            1.0436672 = fieldWeight in 3134, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              5.9038734 = idf(docFreq=327, maxDocs=44218)
              0.125 = fieldNorm(doc=3134)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

0.07713082 = product of:
  0.15426163 = sum of:
    0.15426163 = product of:
      0.30852327 = sum of:
        0.30852327 = weight(_text_:tagging in 703) [ClassicSimilarity], result of:
          0.30852327 = score(doc=703,freq=14.0), product of:
            0.2979515 = queryWeight, product of:
              5.9038734 = idf(docFreq=327, maxDocs=44218)
              0.05046712 = queryNorm
            1.0354816 = fieldWeight in 703, product of:
              3.7416575 = tf(freq=14.0), with freq of:
                14.0 = termFreq=14.0
              5.9038734 = idf(docFreq=327, maxDocs=44218)
              0.046875 = fieldNorm(doc=703)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Abstract

Although user tagging of library resources shows substantial promise as a means of improving the quality of users' access to those resources, several important questions about the level and nature of the warrant for basing retrieval tools on user tagging are yet to receive full consideration by library practitioners and researchers. Among these is the simple evaluative question: What, specifically, are the factors that determine whether or not user-tagging services will be successful? If success is to be defined in terms of the effectiveness with which systems perform the particular functions expected of them (rather than simply in terms of popularity), an understanding is needed both of the multifunctional nature of tagging tools, and of the complex nature of users' mental models of that multifunctionality. In this paper, a conceptual framework is developed for the evaluation of systems that integrate user tagging with more traditional methods of library resource description.

Theme

Social tagging

0.067325294 = product of:
  0.13465059 = sum of:
    0.13465059 = product of:
      0.26930118 = sum of:
        0.26930118 = weight(_text_:tagging in 529) [ClassicSimilarity], result of:
          0.26930118 = score(doc=529,freq=6.0), product of:
            0.2979515 = queryWeight, product of:
              5.9038734 = idf(docFreq=327, maxDocs=44218)
              0.05046712 = queryNorm
            0.9038424 = fieldWeight in 529, product of:
              2.4494898 = tf(freq=6.0), with freq of:
                6.0 = termFreq=6.0
              5.9038734 = idf(docFreq=327, maxDocs=44218)
              0.0625 = fieldNorm(doc=529)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Abstract

The aim of the present study was to identify and categorize social tagging trends and developments as revealed by the analysis of library and information science scholarly and professional literature.

Theme

Social tagging

0.067325294 = product of:
  0.13465059 = sum of:
    0.13465059 = product of:
      0.26930118 = sum of:
        0.26930118 = weight(_text_:tagging in 533) [ClassicSimilarity], result of:
          0.26930118 = score(doc=533,freq=24.0), product of:
            0.2979515 = queryWeight, product of:
              5.9038734 = idf(docFreq=327, maxDocs=44218)
              0.05046712 = queryNorm
            0.9038424 = fieldWeight in 533, product of:
              4.8989797 = tf(freq=24.0), with freq of:
                24.0 = termFreq=24.0
              5.9038734 = idf(docFreq=327, maxDocs=44218)
              0.03125 = fieldNorm(doc=533)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Abstract

Recently, a growing amount of systems that allow personal content annotation (tagging) are being created, ranging from personal sites for organising bookmarks (del.icio.us), photos (flickr.com) or videos (video.google.com, youtube.com) to systems for managing bibliographies for scientific research projects (citeulike.org, connotea.org). Simultaneously, a debate on the pro and cons of allowing users to add personal keywords to digital content has arisen. One recurrent point-of-discussion is whether tagging can solve the well-known vocabulary problem: In order to support successful retrieval in complex environments, it is necessary to index an object with a variety of aliases (cf. Furnas 1987). In this spirit, social tagging enhances the pool of rigid, traditional keywording by adding user-created retrieval vocabularies. Furthermore, tagging goes beyond simple personal content-based keywords by providing meta-keywords like funny or interesting that "identify qualities or characteristics" (Golder and Huberman 2006, Kipp and Campbell 2006, Kipp 2007, Feinberg 2006, Kroski 2005). Contrarily, tagging systems are claimed to lead to semantic difficulties that may hinder the precision and recall of tagging systems (e.g. the polysemy problem, cf. Marlow 2006, Lakoff 2005, Golder and Huberman 2006). Empirical research on social tagging is still rare and mostly from a computer linguistics or librarian point-of-view (Voß 2007) which focus either on the automatic statistical analyses of large data sets, or intellectually inspect single cases of tag usage: Some scientists studied the evolution of tag vocabularies and tag distribution in specific systems (Golder and Huberman 2006, Hammond 2005). Others concentrate on tagging behaviour and tagger characteristics in collaborative systems. (Hammond 2005, Kipp and Campbell 2007, Feinberg 2006, Sen 2006). However, little research has been conducted on the functional and linguistic characteristics of tags.1 An analysis of these patterns could show differences between user wording and conventional keywording. In order to provide a reasonable basis for comparison, a classification system for existing tags is needed.
Therefore our main research questions are as follows: - Is it possible to discover regular patterns in tag usage and to establish a stable category model? - Does a specific tagging language comparable to internet slang or chatspeak evolve? - How do social tags differ from traditional (author / expert) keywords? - To what degree are social tags taken from or findable in the full text of the tagged resource? - Do tags in a research literature context go beyond simple content description (e.g. tags indicating time or task-related information, cf. Kipp et al. 2006)?

Theme

Social tagging

0.066795975 = product of:
  0.13359195 = sum of:
    0.13359195 = product of:
      0.40077582 = sum of:
        0.40077582 = weight(_text_:3a in 1826) [ClassicSimilarity], result of:
          0.40077582 = score(doc=1826,freq=2.0), product of:
            0.4278608 = queryWeight, product of:
              8.478011 = idf(docFreq=24, maxDocs=44218)
              0.05046712 = queryNorm
            0.93669677 = fieldWeight in 1826, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              8.478011 = idf(docFreq=24, maxDocs=44218)
              0.078125 = fieldNorm(doc=1826)
      0.33333334 = coord(1/3)
  0.5 = coord(1/2)

Source

http://www.google.de/url?sa=t&rct=j&q=&esrc=s&source=web&cd=5&ved=0CDQQFjAE&url=http%3A%2F%2Fdigbib.ubka.uni-karlsruhe.de%2Fvolltexte%2Fdocuments%2F3131107&ei=HzFWVYvGMsiNsgGTyoFI&usg=AFQjCNE2FHUeR9oQTQlNC4TPedv4Mo3DaQ&sig2=Rlzpr7a3BLZZkqZCXXN_IA&bvm=bv.93564037,d.bGg&cad=rja

0.06568184 = product of:
  0.13136367 = sum of:
    0.13136367 = sum of:
      0.09717569 = weight(_text_:tagging in 1291) [ClassicSimilarity], result of:
        0.09717569 = score(doc=1291,freq=2.0), product of:
          0.2979515 = queryWeight, product of:
            5.9038734 = idf(docFreq=327, maxDocs=44218)
            0.05046712 = queryNorm
          0.326146 = fieldWeight in 1291, product of:
            1.4142135 = tf(freq=2.0), with freq of:
              2.0 = termFreq=2.0
            5.9038734 = idf(docFreq=327, maxDocs=44218)
            0.0390625 = fieldNorm(doc=1291)
      0.03418799 = weight(_text_:22 in 1291) [ClassicSimilarity], result of:
        0.03418799 = score(doc=1291,freq=2.0), product of:
          0.17672725 = queryWeight, product of:
            3.5018296 = idf(docFreq=3622, maxDocs=44218)
            0.05046712 = 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)

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".

Theme

Social tagging

0.05830541 = product of:
  0.11661082 = sum of:
    0.11661082 = product of:
      0.23322164 = sum of:
        0.23322164 = weight(_text_:tagging in 570) [ClassicSimilarity], result of:
          0.23322164 = score(doc=570,freq=2.0), product of:
            0.2979515 = queryWeight, product of:
              5.9038734 = idf(docFreq=327, maxDocs=44218)
              0.05046712 = queryNorm
            0.78275037 = fieldWeight in 570, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              5.9038734 = idf(docFreq=327, maxDocs=44218)
              0.09375 = fieldNorm(doc=570)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

0.05343678 = product of:
  0.10687356 = sum of:
    0.10687356 = product of:
      0.32062066 = sum of:
        0.32062066 = weight(_text_:3a in 230) [ClassicSimilarity], result of:
          0.32062066 = score(doc=230,freq=2.0), product of:
            0.4278608 = queryWeight, product of:
              8.478011 = idf(docFreq=24, maxDocs=44218)
              0.05046712 = queryNorm
            0.7493574 = fieldWeight in 230, 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=230)
      0.33333334 = coord(1/3)
  0.5 = coord(1/2)

Source

https%3A%2F%2Ftannerlectures.utah.edu%2F_documents%2Fa-to-z%2Fp%2Fpopper80.pdf&usg=AOvVaw3f4QRTEH-OEBmoYr2J_c7H

0.05049397 = product of:
  0.10098794 = sum of:
    0.10098794 = product of:
      0.20197588 = sum of:
        0.20197588 = weight(_text_:tagging in 1061) [ClassicSimilarity], result of:
          0.20197588 = score(doc=1061,freq=6.0), product of:
            0.2979515 = queryWeight, product of:
              5.9038734 = idf(docFreq=327, maxDocs=44218)
              0.05046712 = queryNorm
            0.6778818 = fieldWeight in 1061, product of:
              2.4494898 = tf(freq=6.0), with freq of:
                6.0 = termFreq=6.0
              5.9038734 = idf(docFreq=327, maxDocs=44218)
              0.046875 = fieldNorm(doc=1061)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Abstract

The object of Information Retrieval is to retrieve all relevant documents for a user query and only those relevant documents. Much research has focused on achieving this objective with little regard for storage overhead or performance. In the paper we evaluate the use of Part of Speech Tagging to improve, the index storage overhead and general speed of the system with only a minimal reduction to precision recall measurements. We tagged 500Mbs of the Los Angeles Times 1990 and 1989 document collection provided by TREC for parts of speech. We then experimented to find the most relevant part of speech to index. We show that 90% of precision recall is achieved with 40% of the document collections terms. We also show that this is a improvement in overhead with only a 1% reduction in precision recall.

Object

POS-Tagging

0.048099514 = product of:
  0.09619903 = sum of:
    0.09619903 = product of:
      0.19239806 = sum of:
        0.19239806 = weight(_text_:tagging in 531) [ClassicSimilarity], result of:
          0.19239806 = score(doc=531,freq=4.0), product of:
            0.2979515 = queryWeight, product of:
              5.9038734 = idf(docFreq=327, maxDocs=44218)
              0.05046712 = queryNorm
            0.64573616 = fieldWeight in 531, product of:
              2.0 = tf(freq=4.0), with freq of:
                4.0 = termFreq=4.0
              5.9038734 = idf(docFreq=327, maxDocs=44218)
              0.0546875 = fieldNorm(doc=531)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Abstract

KoT (Kinds of Tags) is an ongoing joint collaborative research effort with many participants worldwide, including the University of Minho, UKOLN, the University of Bologna, the Université Libre de Bruxelles and La Universidad Carlos III de Madrid. It is focused on the analysis of tags that are in common use in the practice of social tagging, with the aim of discovering how easily tags can be 'normalised' for interoperability with standard metadata environments such as the DC Metadata Terms.

Theme

Social tagging

0.04207831 = product of:
  0.08415662 = sum of:
    0.08415662 = product of:
      0.16831324 = sum of:
        0.16831324 = weight(_text_:tagging in 2813) [ClassicSimilarity], result of:
          0.16831324 = score(doc=2813,freq=6.0), product of:
            0.2979515 = queryWeight, product of:
              5.9038734 = idf(docFreq=327, maxDocs=44218)
              0.05046712 = queryNorm
            0.5649015 = fieldWeight in 2813, product of:
              2.4494898 = tf(freq=6.0), with freq of:
                6.0 = termFreq=6.0
              5.9038734 = idf(docFreq=327, maxDocs=44218)
              0.0390625 = fieldNorm(doc=2813)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Abstract

Today, in times of Web 2.0., graduates and undergraduates interact in virtual communities like studiVZ (Studentenverzeichnis) and generate content by reviewing or tagging documents. This phenomenon offers good prospects for academic libraries. They can use the customers' tags for indexing the growing amount of electronic resources and thereby optimize the search for these documents. Important examples are the journals, databases and e-books included in the "Nationallizenzen" financed by the German Research Foundation (DFG). The documents in this collection are not manually indexed by librarians and have no annotation according to the German standard classification systems. Connecting search systems by means of Web-2.0.-services is an important task for libraries. For this purpose users are encouraged to tag printed and electronic resources in search systems like the libraries' online catalogs and to establish connections between entries in other systems, e.g. Bibsonomy, and the items found in the online catalog. As a consequence annotations chosen by both, users and librarians, will coexist: The items in the tagging systems and the online catalog are linked, library users may find other publications of interest, and contacts between library users with similar scientific interests may be established. Librarians have to face the fact that user generated tags do not necessarily have the same quality as their own annotations and will therefore have to seek for instruments for comparing user generated tags with library generated keywords.

Theme

Social tagging

0.038870275 = product of:
  0.07774055 = sum of:
    0.07774055 = product of:
      0.1554811 = sum of:
        0.1554811 = weight(_text_:tagging in 1666) [ClassicSimilarity], result of:
          0.1554811 = score(doc=1666,freq=2.0), product of:
            0.2979515 = queryWeight, product of:
              5.9038734 = idf(docFreq=327, maxDocs=44218)
              0.05046712 = queryNorm
            0.5218336 = fieldWeight in 1666, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              5.9038734 = idf(docFreq=327, maxDocs=44218)
              0.0625 = fieldNorm(doc=1666)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Abstract

Autonomy's Classification solutions remove the necessity for organizations to rely on human intervention or manual processing of information, such as manual tagging, typically required to make most other e-business applications work. Autonomy's ability to consistently and accurately classify data automatically is a unique infrastructure solution that overcomes the predicaments surrounding the exponential growth of unstructured data.

0.038870275 = product of:
  0.07774055 = sum of:
    0.07774055 = product of:
      0.1554811 = sum of:
        0.1554811 = weight(_text_:tagging in 124) [ClassicSimilarity], result of:
          0.1554811 = score(doc=124,freq=2.0), product of:
            0.2979515 = queryWeight, product of:
              5.9038734 = idf(docFreq=327, maxDocs=44218)
              0.05046712 = queryNorm
            0.5218336 = fieldWeight in 124, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              5.9038734 = idf(docFreq=327, maxDocs=44218)
              0.0625 = fieldNorm(doc=124)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

0.038870275 = product of:
  0.07774055 = sum of:
    0.07774055 = product of:
      0.1554811 = sum of:
        0.1554811 = weight(_text_:tagging in 657) [ClassicSimilarity], result of:
          0.1554811 = score(doc=657,freq=2.0), product of:
            0.2979515 = queryWeight, product of:
              5.9038734 = idf(docFreq=327, maxDocs=44218)
              0.05046712 = queryNorm
            0.5218336 = fieldWeight in 657, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              5.9038734 = idf(docFreq=327, maxDocs=44218)
              0.0625 = fieldNorm(doc=657)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Abstract

The UCLA Library reorganized its software developers into focused subteams with one, the Labs Team, dedicated to conducting experiments. In this article we describe our first attempt at conducting a software development experiment, in which we attempted to improve our digital library's search results with metadata from cloud-based image tagging services. We explore the findings and discuss the lessons learned from our first attempt at running an experiment.

0.034356795 = product of:
  0.06871359 = sum of:
    0.06871359 = product of:
      0.13742718 = sum of:
        0.13742718 = weight(_text_:tagging in 1265) [ClassicSimilarity], result of:
          0.13742718 = score(doc=1265,freq=4.0), product of:
            0.2979515 = queryWeight, product of:
              5.9038734 = idf(docFreq=327, maxDocs=44218)
              0.05046712 = queryNorm
            0.4612401 = fieldWeight in 1265, product of:
              2.0 = tf(freq=4.0), with freq of:
                4.0 = termFreq=4.0
              5.9038734 = idf(docFreq=327, maxDocs=44218)
              0.0390625 = fieldNorm(doc=1265)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

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.

Theme

Social tagging

0.029454816 = product of:
  0.058909632 = sum of:
    0.058909632 = product of:
      0.117819265 = sum of:
        0.117819265 = weight(_text_:tagging in 1188) [ClassicSimilarity], result of:
          0.117819265 = score(doc=1188,freq=6.0), product of:
            0.2979515 = queryWeight, product of:
              5.9038734 = idf(docFreq=327, maxDocs=44218)
              0.05046712 = queryNorm
            0.39543104 = fieldWeight in 1188, product of:
              2.4494898 = tf(freq=6.0), with freq of:
                6.0 = termFreq=6.0
              5.9038734 = idf(docFreq=327, maxDocs=44218)
              0.02734375 = fieldNorm(doc=1188)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

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.
A number of such utilities are presented here, together with an emergent new class of tools that caters more to the academic communities and that stores not only user-supplied tags, but also structured citation metadata terms wherever it is possible to glean this information from service providers. This provision of rich, structured metadata means that the user is provided with an accurate third-party identification of a document, which could be used to retrieve that document, but is also free to search on user-supplied terms so that documents of interest (or rather, references to documents) can be made discoverable and aggregated with other similar descriptions either recorded by the user or by other users. Matt Biddulph in an XML.com article last year, in which he reviews one of the better known social bookmarking tools, del.icio.us, declares that the "del.icio.us-space has three major axes: users, tags, and URLs". We fully support that assessment but choose to present this deconstruction in a reverse order. This paper thus first recaps a brief history of bookmarks, then discusses the current interest in tagging, moves on to look at certain social issues, and finally considers some of the feature sets offered by the new bookmarking tools. A general review of a number of common social bookmarking tools is presented in the annex. A companion paper describes a case study in more detail: the tool that Nature Publishing Group has made available to the scientific community as an experimental entrée into this field - Connotea; our reasons for endeavouring to provide such a utility; and experiences gained and lessons learned.

Theme

Social tagging

0.027485436 = product of:
  0.05497087 = sum of:
    0.05497087 = product of:
      0.10994174 = sum of:
        0.10994174 = weight(_text_:tagging in 705) [ClassicSimilarity], result of:
          0.10994174 = score(doc=705,freq=4.0), product of:
            0.2979515 = queryWeight, product of:
              5.9038734 = idf(docFreq=327, maxDocs=44218)
              0.05046712 = queryNorm
            0.3689921 = fieldWeight in 705, product of:
              2.0 = tf(freq=4.0), with freq of:
                4.0 = termFreq=4.0
              5.9038734 = idf(docFreq=327, maxDocs=44218)
              0.03125 = fieldNorm(doc=705)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Abstract

What is the role of controlled vocabulary in a Web 2.0 world? Can we have the best of both worlds: balancing folksonomies and controlled vocabularies to help communities of users find and share information and resources most relevant to them? education.au develops and manages Australian online services for education and training. Its goal is to bring people, learning and technology together. education.au projects are increasingly involved in exploring the use of Web 2.0 developments building on user ideas, knowledge and experience, and how these might be integrated with existing information management systems. This paper presents work being undertaken in this area, particularly in relation to controlled vocabularies, and discusses the challenges faced. Education Network Australia (edna) is a leading online resource collection and collaborative network for education, with an extensive repository of selected educational resources with metadata created by educators and information specialists. It uses controlled vocabularies for metadata creation and searching, where users receive suggested related terms from an education thesaurus, with their results. We recognise that no formal thesaurus can keep pace with user needs so are interested in exploiting the power of folksonomies. We describe a proof of concept project to develop community contributions to managing information and resources, using Taxonomy-Directed Folksonomy. An established taxonomy from the Australian education sector suggests terms for tagging and users can suggest terms. Importantly, the folksonomy will feed back into the taxonomy showing gaps in coverage and helping us to monitor new terms and usage to improve and develop our formal taxonomies. This model would initially sit alongside the current edna repositories, tools and services but will give us valuable user contributed resources as well as information about how users manage resources. Observing terms suggested, chosen and used in folksonomies is a rich source of information for developing our formal systems so that we can indeed get the best of both worlds.

0.026756335 = product of:
  0.05351267 = sum of:
    0.05351267 = product of:
      0.10702534 = sum of:
        0.10702534 = weight(_text_:22 in 1936) [ClassicSimilarity], result of:
          0.10702534 = score(doc=1936,freq=10.0), product of:
            0.17672725 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.05046712 = queryNorm
            0.6055961 = fieldWeight in 1936, product of:
              3.1622777 = tf(freq=10.0), with freq of:
                10.0 = termFreq=10.0
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.0546875 = fieldNorm(doc=1936)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Abstract

Dewey Decimal Classification and Relative Index, Edition 22 (DDC 22) will be issued simultaneously in print and web versions in July 2003. The new edition is the first full print update to the Dewey Decimal Classification system in seven years-it includes several significant updates and many new numbers and topics. DDC 22 also features some fundamental structural changes that have been introduced with the goals of promoting classifier efficiency and improving the DDC for use in a variety of applications in the web environment. Most importantly, the content of the new edition has been shaped by the needs and recommendations of Dewey users around the world. The worldwide user community has an important role in shaping the future of the DDC.

Object

DDC-22