Search (28 results, page 2 of 2)

  • × theme_ss:"Folksonomies"
  1. 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) 0.01
    0.008823298 = product of:
      0.017646596 = sum of:
        0.017646596 = product of:
          0.03529319 = sum of:
            0.03529319 = weight(_text_:22 in 2650) [ClassicSimilarity], result of:
              0.03529319 = score(doc=2650,freq=2.0), product of:
                0.18244034 = queryWeight, product of:
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.052098576 = 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)
      0.5 = coord(1/2)
    
    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
  2. Chopin, K.: Finding communities : alternative viewpoints through weblogs and tagging (2008) 0.01
    0.007663213 = product of:
      0.015326426 = sum of:
        0.015326426 = product of:
          0.030652853 = sum of:
            0.030652853 = weight(_text_:web in 2341) [ClassicSimilarity], result of:
              0.030652853 = score(doc=2341,freq=2.0), product of:
                0.17002425 = queryWeight, product of:
                  3.2635105 = idf(docFreq=4597, maxDocs=44218)
                  0.052098576 = queryNorm
                0.18028519 = fieldWeight in 2341, 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=2341)
          0.5 = coord(1/2)
      0.5 = coord(1/2)
    
    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.
  3. Pera, M.S.; Lund, W.; Ng, Y.-K.: ¬A sophisticated library search strategy using folksonomies and similarity matching (2009) 0.01
    0.007663213 = product of:
      0.015326426 = sum of:
        0.015326426 = product of:
          0.030652853 = sum of:
            0.030652853 = weight(_text_:web in 2939) [ClassicSimilarity], result of:
              0.030652853 = score(doc=2939,freq=2.0), product of:
                0.17002425 = queryWeight, product of:
                  3.2635105 = idf(docFreq=4597, maxDocs=44218)
                  0.052098576 = queryNorm
                0.18028519 = fieldWeight in 2939, 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=2939)
          0.5 = coord(1/2)
      0.5 = coord(1/2)
    
    Abstract
    Libraries, private and public, offer valuable resources to library patrons. As of today, the only way to locate information archived exclusively in libraries is through their catalogs. Library patrons, however, often find it difficult to formulate a proper query, which requires using specific keywords assigned to different fields of desired library catalog records, to obtain relevant results. These improperly formulated queries often yield irrelevant results or no results at all. This negative experience in dealing with existing library systems turns library patrons away from directly querying library catalogs; instead, they rely on Web search engines to perform their searches first, and upon obtaining the initial information (e.g., titles, subject headings, or authors) on the desired library materials, they query library catalogs. This searching strategy is an evidence of failure of today's library systems. In solving this problem, we propose an enhanced library system, which allows partial, similarity matching of (a) tags defined by ordinary users at a folksonomy site that describe the content of books and (b) unrestricted keywords specified by an ordinary library patron in a query to search for relevant library catalog records. The proposed library system allows patrons posting a query Q using commonly used words and ranks the retrieved results according to their degrees of resemblance with Q while maintaining the query processing time comparable with that achieved by current library search engines.
  4. Sauperl, A.: UDC and Folksonomies (2010) 0.01
    0.007663213 = product of:
      0.015326426 = sum of:
        0.015326426 = product of:
          0.030652853 = sum of:
            0.030652853 = weight(_text_:web in 4069) [ClassicSimilarity], result of:
              0.030652853 = score(doc=4069,freq=2.0), product of:
                0.17002425 = queryWeight, product of:
                  3.2635105 = idf(docFreq=4597, maxDocs=44218)
                  0.052098576 = queryNorm
                0.18028519 = fieldWeight in 4069, 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=4069)
          0.5 = coord(1/2)
      0.5 = coord(1/2)
    
    Abstract
    Social tagging systems, known as "folksonomies," represent an important part of web resource discovery as they enable free and unrestricted browsing through information space. Folksonomies consisting of subject designators (tags) assigned by users, however, have one important drawback: they do not express semantic relationships, either hierarchical or associative, between tags. As a consequence, the use of tags to browse information resources requires moving from one resource to another, based on coincidence and not on the pre-established meaningful or logical connections that may exist between related resources. We suggest that the semantic structure of the Universal Decimal Classification (UDC) may be used in complementing and supporting tag-based browsing. In this work, two specific questions were investigated: 1) Are terms used as tags in folksonomies included in the UDC?; and, 2) Which facets of UDC match the characteristics of documents or information objects that are tagged in folksonomies? A collection of the most popular tags from Amazon, LibraryThing, Delicious, and 43Things was investigated. The universal nature of UDC was examined through the universality of topics and facets covering diverse human interests which are at the same time interconnected and form a rich and intricate semantic structure. The results suggest that UDC-supported folksonomies could be implemented in resource discovery, in particular in library portals and catalogues.
  5. Peters, I.; Stock, W.G.: Power tags in information retrieval (2010) 0.01
    0.007663213 = product of:
      0.015326426 = sum of:
        0.015326426 = product of:
          0.030652853 = sum of:
            0.030652853 = weight(_text_:web in 865) [ClassicSimilarity], result of:
              0.030652853 = score(doc=865,freq=2.0), product of:
                0.17002425 = queryWeight, product of:
                  3.2635105 = idf(docFreq=4597, maxDocs=44218)
                  0.052098576 = queryNorm
                0.18028519 = fieldWeight in 865, 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=865)
          0.5 = coord(1/2)
      0.5 = coord(1/2)
    
    Abstract
    Purpose - Many Web 2.0 services (including Library 2.0 catalogs) make use of folksonomies. The purpose of this paper is to cut off all tags in the long tail of a document-specific tag distribution. The remaining tags at the beginning of a tag distribution are considered power tags and form a new, additional search option in information retrieval systems. Design/methodology/approach - In a theoretical approach the paper discusses document-specific tag distributions (power law and inverse-logistic shape), the development of such distributions (Yule-Simon process and shuffling theory) and introduces search tags (besides the well-known index tags) as a possibility for generating tag distributions. Findings - Search tags are compatible with broad and narrow folksonomies and with all knowledge organization systems (e.g. classification systems and thesauri), while index tags are only applicable in broad folksonomies. Based on these findings, the paper presents a sketch of an algorithm for mining and processing power tags in information retrieval systems. Research limitations/implications - This conceptual approach is in need of empirical evaluation in a concrete retrieval system. Practical implications - Power tags are a new search option for retrieval systems to limit the amount of hits. Originality/value - The paper introduces power tags as a means for enhancing the precision of search results in information retrieval systems that apply folksonomies, e.g. catalogs in Library 2.0environments.
  6. Braun, M.: Lesezeichen zum Stöbern : "Social bookmark"-Seiten setzen auf die Empfehlungen ihrer Nutzer (2007) 0.01
    0.007058638 = product of:
      0.014117276 = sum of:
        0.014117276 = product of:
          0.028234553 = sum of:
            0.028234553 = weight(_text_:22 in 3373) [ClassicSimilarity], result of:
              0.028234553 = score(doc=3373,freq=2.0), product of:
                0.18244034 = queryWeight, product of:
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.052098576 = queryNorm
                0.15476047 = fieldWeight in 3373, 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=3373)
          0.5 = coord(1/2)
      0.5 = coord(1/2)
    
    Date
    3. 5.1997 8:44:22
  7. Yi, K.; Chan, L.M.: Linking folksonomy to Library of Congress subject headings : an exploratory study (2009) 0.01
    0.0061305705 = product of:
      0.012261141 = sum of:
        0.012261141 = product of:
          0.024522282 = sum of:
            0.024522282 = weight(_text_:web in 3616) [ClassicSimilarity], result of:
              0.024522282 = score(doc=3616,freq=2.0), product of:
                0.17002425 = queryWeight, product of:
                  3.2635105 = idf(docFreq=4597, maxDocs=44218)
                  0.052098576 = queryNorm
                0.14422815 = fieldWeight in 3616, 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=3616)
          0.5 = coord(1/2)
      0.5 = coord(1/2)
    
    Abstract
    Purpose - The purpose of this paper is to investigate the linking of a folksonomy (user vocabulary) and LCSH (controlled vocabulary) on the basis of word matching, for the potential use of LCSH in bringing order to folksonomies. Design/methodology/approach - A selected sample of a folksonomy from a popular collaborative tagging system, Delicious, was word-matched with LCSH. LCSH was transformed into a tree structure called an LCSH tree for the matching. A close examination was conducted on the characteristics of folksonomies, the overlap of folksonomies with LCSH, and the distribution of folksonomies over the LCSH tree. Findings - The experimental results showed that the total proportion of tags being matched with LC subject headings constituted approximately two-thirds of all tags involved, with an additional 10 percent of the remaining tags having potential matches. A number of barriers for the linking as well as two areas in need of improving the matching are identified and described. Three important tag distribution patterns over the LCSH tree were identified and supported: skewedness, multifacet, and Zipfian-pattern. Research limitations/implications - The results of the study can be adopted for the development of innovative methods of mapping between folksonomy and LCSH, which directly contributes to effective access and retrieval of tagged web resources and to the integration of multiple information repositories based on the two vocabularies. Practical implications - The linking of controlled vocabularies can be applicable to enhance information retrieval capability within collaborative tagging systems as well as across various tagging system information depositories and bibliographic databases. Originality/value - This is among frontier works that examines the potential of linking a folksonomy, extracted from a collaborative tagging system, to an authority-maintained subject heading system. It provides exploratory data to support further advanced mapping methods for linking the two vocabularies.
  8. Xie, H.; Li, X.; Wang, T.; Lau, R.Y.K.; Wong, T.-L.; Chen, L.; Wang, F.L.; Li, Q.: Incorporating sentiment into tag-based user profiles and resource profiles for personalized search in folksonomy (2016) 0.01
    0.0061305705 = product of:
      0.012261141 = sum of:
        0.012261141 = product of:
          0.024522282 = sum of:
            0.024522282 = weight(_text_:web in 2671) [ClassicSimilarity], result of:
              0.024522282 = score(doc=2671,freq=2.0), product of:
                0.17002425 = queryWeight, product of:
                  3.2635105 = idf(docFreq=4597, maxDocs=44218)
                  0.052098576 = queryNorm
                0.14422815 = fieldWeight in 2671, 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=2671)
          0.5 = coord(1/2)
      0.5 = coord(1/2)
    
    Abstract
    In recent years, there has been a rapid growth of user-generated data in collaborative tagging (a.k.a. folksonomy-based) systems due to the prevailing of Web 2.0 communities. To effectively assist users to find their desired resources, it is critical to understand user behaviors and preferences. Tag-based profile techniques, which model users and resources by a vector of relevant tags, are widely employed in folksonomy-based systems. This is mainly because that personalized search and recommendations can be facilitated by measuring relevance between user profiles and resource profiles. However, conventional measurements neglect the sentiment aspect of user-generated tags. In fact, tags can be very emotional and subjective, as users usually express their perceptions and feelings about the resources by tags. Therefore, it is necessary to take sentiment relevance into account into measurements. In this paper, we present a novel generic framework SenticRank to incorporate various sentiment information to various sentiment-based information for personalized search by user profiles and resource profiles. In this framework, content-based sentiment ranking and collaborative sentiment ranking methods are proposed to obtain sentiment-based personalized ranking. To the best of our knowledge, this is the first work of integrating sentiment information to address the problem of the personalized tag-based search in collaborative tagging systems. Moreover, we compare the proposed sentiment-based personalized search with baselines in the experiments, the results of which have verified the effectiveness of the proposed framework. In addition, we study the influences by popular sentiment dictionaries, and SenticNet is the most prominent knowledge base to boost the performance of personalized search in folksonomy.