Discovering Serendipitous Information from Wikipedia by Using Its Network Structure

Authors

  • Yohei Noda University of Tokyo
  • Yoji Kiyota University of Tokyo
  • Hiroshi Nakagawa University of Tokyo

Keywords:

Serendipity, Wikipedia

Abstract

Many researchers conducted studies on extracting relevant information from web documents. However, there are few studies on extracting serendipitous information. We propose methods to discover unexpected information from Wikipedia by using its network structure, for example, the distance between two categories. We evaluated two methods: a classification-based method using support vector machines (SVMs), and a ranking-based method using regression. We demonstrate advantages of regression over classification.

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Published

2010-05-16

How to Cite

Noda, Y., Kiyota, Y., & Nakagawa, H. (2010). Discovering Serendipitous Information from Wikipedia by Using Its Network Structure. Proceedings of the International AAAI Conference on Web and Social Media, 4(1), 299-302. Retrieved from https://ojs.aaai.org/index.php/ICWSM/article/view/14077