ML Anthology

Towards Ontology Learning from Folksonomies

Jie Tang, Ho-fung Leung, Qiong Luo, Dewei Chen, Jibin Gong
IJCAI 2009 pp. 2089-2094
/ijcai/2009/tang2009ijcai-ontology/

Abstract

A folksonomy refers to a collection of user-defined tags with which users describe contents published on the Web. With the flourish of Web 2.0, folksonomies have become an important mean to develop the Semantic Web. Because tags in folksonomies are authored freely, there is a need to understand the structure and semantics of these tags in various applications. In this paper, we propose a learning approach to create an ontology that captures the hierarchical semantic structure of folksonomies. Our experimental results on two different genres of real world data sets show that our method can effectively learn the ontology structure from the folksonomies. Jie Tang, Ho-fung Leung, Qiong Luo, Dewei Chen, Jibin Gong

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Text

Tang et al. "Towards Ontology Learning from Folksonomies." International Joint Conference on Artificial Intelligence, 2009.

Markdown

[Tang et al. "Towards Ontology Learning from Folksonomies." International Joint Conference on Artificial Intelligence, 2009.](https://mlanthology.org/ijcai/2009/tang2009ijcai-ontology/)

BibTeX

@inproceedings{tang2009ijcai-ontology,
  title     = {{Towards Ontology Learning from Folksonomies}},
  author    = {Tang, Jie and Leung, Ho-fung and Luo, Qiong and Chen, Dewei and Gong, Jibin},
  booktitle = {International Joint Conference on Artificial Intelligence},
  year      = {2009},
  pages     = {2089-2094},
  url       = {https://mlanthology.org/ijcai/2009/tang2009ijcai-ontology/}
}