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An Unsupervised Model for Exploring Hierarchical Semantics from Social Annotations

by: Mianwei Zhou, Shenghua Bao, Xian Wu, and Yong Yu

In: Proceedings of the 6th International Semantic Web Conference and 2nd Asian Semantic Web Conference ISWC/ASWC2007, Busan, South Korea, Vol. 4825 Berlin, Heidelberg: Springer Verlag (November 2007) , p. 673--686.

Resources (URL, PDF, PS...)

URL:	http://iswc2007.semanticweb.org/papers/673.pdf

Abstract

This paper deals with the problem of exploring hierarchical semantics from social annotations. Recently, social annotation services have become more and more popular in Semantic Web. It allows users to arbitrarily annotate web resources, thus, largely lowers the barrier to cooperation. Furthermore, through providing abundant meta-data resources, social annotation might become a key to the development of Semantic Web. However, on the other hand, social annotation has its own apparent limitations, for instance, 1 ambiguity and synonym phenomena and 2 lack of hierarchical information. In this paper, we propose an unsupervised model to automatically derive hierarchical semantics from social annotations. Using a social bookmark service Del.icio.us as example, we demonstrate that the derived hierarchical semantics has the ability to compensate those shortcomings. We further apply our model on another data set from Flickr to testify our model's applicability on different environments. The experimental results demonstrate our model's effciency.

BibTeX record

@inproceedings{Zhou/2007/Unsupervised,
  abstract = {This paper deals with the problem of exploring hierarchical semantics from social annotations. Recently, social annotation services have become more and more popular in Semantic Web. It allows users to arbitrarily annotate web resources, thus, largely lowers the barrier to cooperation. Furthermore, through providing abundant meta-data resources, social annotation might become a key to the development of Semantic Web. However, on the other hand, social annotation has its own apparent limitations, for instance, 1) ambiguity and synonym phenomena and 2) lack of hierarchical information. In this paper, we propose an unsupervised model to automatically derive hierarchical semantics from social annotations. Using a social bookmark service Del.icio.us as example, we demonstrate that the derived hierarchical semantics has the ability to compensate those shortcomings. We further apply our model on another data set from Flickr to testify our model's applicability on different environments. The experimental results demonstrate our model's effciency.},
  added-at = {2010-03-20T21:45:30.000+0100},
  address = {Berlin, Heidelberg},
  author = {Zhou, Mianwei and Bao, Shenghua and Wu, Xian and Yu, Yong},
  biburl = {http://www.bibsonomy.org/bibtex/2355fcbb32255f3ba5f41819c00c520ba/hotho},
  booktitle = {Proceedings of the 6th International Semantic Web Conference and 2nd Asian Semantic Web Conference (ISWC/ASWC2007), Busan, South Korea},
  crossref = {http://data.semanticweb.org/conference/iswc-aswc/2007/proceedings},
  editor = {Aberer, Karl and Choi, Key-Sun and Noy, Natasha and Allemang, Dean and Lee, Kyung-Il and Nixon, Lyndon J B and Golbeck, Jennifer and Mika, Peter and Maynard, Diana and Schreiber, Guus and Cudré-Mauroux, Philippe},
  interhash = {af21595ee9f4a13b5e651ad049f31262},
  intrahash = {355fcbb32255f3ba5f41819c00c520ba},
  keywords = {folksonomy ol semantic tagging taggingsurvey},
  month = {November},
  pages = {673--686},
  publisher = {Springer Verlag},
  series = {LNCS},
  timestamp = {2010-03-20T21:45:30.000+0100},
  title = {An Unsupervised Model for Exploring Hierarchical Semantics from Social Annotations},
  url = {http://iswc2007.semanticweb.org/papers/673.pdf},
  volume = 4825,
  year = 2007
}

Endnote record

%0 Conference Paper
%1 Zhou/2007/Unsupervised
%A Zhou, Mianwei
%A Bao, Shenghua
%A Wu, Xian
%A Yu, Yong
%B Proceedings of the 6th International Semantic Web Conference and 2nd Asian Semantic Web Conference (ISWC/ASWC2007), Busan, South Korea
%C Berlin, Heidelberg
%D 2007
%E Aberer, Karl
%E Choi, Key-Sun
%E Noy, Natasha
%E Allemang, Dean
%E Lee, Kyung-Il
%E Nixon, Lyndon J B
%E Golbeck, Jennifer
%E Mika, Peter
%E Maynard, Diana
%E Schreiber, Guus
%E Cudré-Mauroux, Philippe
%I Springer Verlag
%K 
%P 673--686
%T An Unsupervised Model for Exploring Hierarchical Semantics from Social Annotations
%U http://iswc2007.semanticweb.org/papers/673.pdf
%V 4825
%X This paper deals with the problem of exploring hierarchical semantics from social annotations. Recently, social annotation services have become more and more popular in Semantic Web. It allows users to arbitrarily annotate web resources, thus, largely lowers the barrier to cooperation. Furthermore, through providing abundant meta-data resources, social annotation might become a key to the development of Semantic Web. However, on the other hand, social annotation has its own apparent limitations, for instance, 1) ambiguity and synonym phenomena and 2) lack of hierarchical information. In this paper, we propose an unsupervised model to automatically derive hierarchical semantics from social annotations. Using a social bookmark service Del.icio.us as example, we demonstrate that the derived hierarchical semantics has the ability to compensate those shortcomings. We further apply our model on another data set from Flickr to testify our model's applicability on different environments. The experimental results demonstrate our model's effciency.