2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM) (2016)
San Francisco, CA, USA
Aug. 18, 2016 to Aug. 21, 2016
Taesung Lee , Yonsei University Seoul, Republic of Korea
Seung-won Hwang , Yonsei University Seoul, Republic of Korea
Zhongyuan Wang , Microsoft Research Beijing, China
Recent work suggests that providing unexpected information is an important factor for drawing user traffic. Such examples can be easily found in the “Did you know” section of the Wikipedia main page, the ESPN quiz, the Google Doodles, and the Bing main page. Inspired by these applications, we propose a novel trivia quiz mining asking unexpected questions for a given entity. We solve this problem by linking different types of social media as input and output, and mine unexpected properties based on prototype theory to mediate the input and the output media.
Neck, Prototypes, Knowledge based systems, Flickr, Dogs, Probabilistic logic, Encyclopedias
T. Lee, S. Hwang and Z. Wang, "Trivia quiz mining using probabilistic knowledge," 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM), San Francisco, CA, USA, 2016, pp. 1392-1393.