One Tag to Bind Them All: Measuring Term Abstractness in Social Metadata?

Recent research has demonstrated how the widespread adoption of collaborative tagging systems yields emergent semantics. In recent years, much has been learned about how to harvest the data produced by taggers for engineering light-weight ontologies. For example, existing measures of tag similarity and tag relatedness have proven crucial step stones for making latent semantic relations in tagging systems explicit. However, little progress has been made on other issues, such as understanding the different levels of tag generality (or tag abstractness), which is essential for, among others, identifying hierarchical relationships between concepts. In this paper we aim to address this gap. Starting from a review of linguistic definitions of word abstractness, we first use several large-scale ontologies and taxonomies as grounded measures of word generality, including Yago, Wordnet, DMOZ and WikiTaxonomy. Then, we introduce and apply several folksonomy-based methods to measure the level of generality of given tags. We evaluate these methods by comparing them with the grounded measures. Our results suggest that the generality of tags in social tagging systems can be approximated with simple measures. Our work has implications for a number of problems related to social tagging systems, including search, tag recommendation, and the acquisition of light-weight ontologies from tagging data.

[1]  Allan Paivio,et al.  Extensions of the Paivio, Yuille, and Madigan (1968) norms , 2004, Behavior research methods, instruments, & computers : a journal of the Psychonomic Society, Inc.

[2]  Steffen Staab,et al.  KAON - Towards a Large Scale Semantic Web , 2002, EC-Web.

[3]  Simone Paolo Ponzetto,et al.  Deriving a Large-Scale Taxonomy from Wikipedia , 2007, AAAI.

[4]  Gerhard Weikum,et al.  WWW 2007 / Track: Semantic Web Session: Ontologies ABSTRACT YAGO: A Core of Semantic Knowledge , 2022 .

[5]  Wei Lee Woon,et al.  Comparison of generality based algorithm variants for automatic taxonomy generation , 2009, 2009 International Conference on Innovations in Information Technology (IIT).

[6]  Andreas Hotho,et al.  Information Retrieval in Folksonomies: Search and Ranking , 2006, ESWC.

[7]  Qiao Zhang,et al.  Fuzziness - vagueness - generality - ambiguity , 1998 .

[8]  Peter Mika Ontologies Are Us: A Unified Model of Social Networks and Semantics , 2005, International Semantic Web Conference.

[9]  Dominik Benz,et al.  Stop thinking, start tagging: tag semantics emerge from collaborative verbosity , 2010, WWW '10.

[10]  Ciro Cattuto,et al.  Semantic Analysis of Tag Similarity Measures in Collaborative Tagging Systems , 2008, LWA.

[11]  J. Fleiss Measuring nominal scale agreement among many raters. , 1971 .

[12]  Ulrik Brandes,et al.  Centrality Estimation in Large Networks , 2007, Int. J. Bifurc. Chaos.

[13]  Stanley Wasserman,et al.  Social Network Analysis: Methods and Applications , 1994, Structural analysis in the social sciences.

[14]  A. Paivio,et al.  Concreteness, imagery, and meaningfulness values for 925 nouns. , 1968, Journal of experimental psychology.

[15]  Dominik Benz,et al.  Semantics made by you and me: Self-emerging ontologies can capture the diversity of shared knowledge , 2010 .

[16]  Lynn A. Streeter,et al.  Two meanings of word abstractness , 1971 .

[17]  Edward A. Fox,et al.  Digital Libraries: People, Knowledge, and Technology , 2002, Lecture Notes in Computer Science.

[18]  Hector Garcia-Molina,et al.  Social tag prediction , 2008, SIGIR '08.

[19]  Eyke Hüllermeier,et al.  Predicting Partial Orders: Ranking with Abstention , 2010, ECML/PKDD.

[20]  P. Schmitz,et al.  Inducing Ontology from Flickr Tags , 2006 .

[21]  Christiane Fellbaum,et al.  Book Reviews: WordNet: An Electronic Lexical Database , 1999, CL.

[22]  Steffen Staab,et al.  Ontology Learning for the Semantic Web , 2002, IEEE Intell. Syst..

[23]  Steffen Staab,et al.  Learning Concept Hierarchies from Text Corpora using Formal Concept Analysis , 2005, J. Artif. Intell. Res..

[24]  Bernardo A. Huberman,et al.  Usage patterns of collaborative tagging systems , 2006, J. Inf. Sci..

[25]  Hector Garcia-Molina,et al.  Collaborative Creation of Communal Hierarchical Taxonomies in Social Tagging Systems , 2006 .

[26]  Robert B. Allen,et al.  Generality of Texts , 2002, ICADL.