Trivia quiz mining using probabilistic knowledge

Taesung Lee; Seung Won Hwang; Zhongyuan Wang

doi:10.1109/ASONAM.2016.7752427

Trivia quiz mining using probabilistic knowledge

Taesung Lee, Seung Won Hwang, Zhongyuan Wang

College of Computing

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

2 Citations (Scopus)

Abstract

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.

Original language	English
Title of host publication	Proceedings of the 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2016
Editors	Ravi Kumar, James Caverlee, Hanghang Tong
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	1392-1393
Number of pages	2
ISBN (Electronic)	9781509028467
DOIs	https://doi.org/10.1109/ASONAM.2016.7752427
Publication status	Published - 2016 Nov 21
Event	2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2016 - San Francisco, United States Duration: 2016 Aug 18 → 2016 Aug 21

Publication series

Name	Proceedings of the 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2016

Other

Other	2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2016
Country/Territory	United States
City	San Francisco
Period	16/8/18 → 16/8/21

Bibliographical note

Funding Information:
This work was supported by a grant of the Institute for Information and Communications Technology Promotion (IITP) funded by the Korea government (MSIP) (No. 10041244, SmartTV 2.0 Software Platform)

Publisher Copyright:
© 2016 IEEE.

All Science Journal Classification (ASJC) codes

Computer Networks and Communications
Sociology and Political Science
Communication

Access to Document

10.1109/ASONAM.2016.7752427

Cite this

Lee, T., Hwang, S. W., & Wang, Z. (2016). Trivia quiz mining using probabilistic knowledge. In R. Kumar, J. Caverlee, & H. Tong (Eds.), Proceedings of the 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2016 (pp. 1392-1393). [7752427] (Proceedings of the 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2016). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ASONAM.2016.7752427

Lee, Taesung ; Hwang, Seung Won ; Wang, Zhongyuan. / Trivia quiz mining using probabilistic knowledge. Proceedings of the 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2016. editor / Ravi Kumar ; James Caverlee ; Hanghang Tong. Institute of Electrical and Electronics Engineers Inc., 2016. pp. 1392-1393 (Proceedings of the 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2016).

@inproceedings{4d70ee5ca5a847a0a72928a12682b6c3,

title = "Trivia quiz mining using probabilistic knowledge",

abstract = "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.",

author = "Taesung Lee and Hwang, {Seung Won} and Zhongyuan Wang",

note = "Funding Information: This work was supported by a grant of the Institute for Information and Communications Technology Promotion (IITP) funded by the Korea government (MSIP) (No. 10041244, SmartTV 2.0 Software Platform) Publisher Copyright: {\textcopyright} 2016 IEEE.; 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2016 ; Conference date: 18-08-2016 Through 21-08-2016",

year = "2016",

month = nov,

day = "21",

doi = "10.1109/ASONAM.2016.7752427",

language = "English",

series = "Proceedings of the 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2016",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "1392--1393",

editor = "Ravi Kumar and James Caverlee and Hanghang Tong",

booktitle = "Proceedings of the 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2016",

address = "United States",

}

Lee, T, Hwang, SW & Wang, Z 2016, Trivia quiz mining using probabilistic knowledge. in R Kumar, J Caverlee & H Tong (eds), Proceedings of the 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2016., 7752427, Proceedings of the 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2016, Institute of Electrical and Electronics Engineers Inc., pp. 1392-1393, 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2016, San Francisco, United States, 16/8/18. https://doi.org/10.1109/ASONAM.2016.7752427

Trivia quiz mining using probabilistic knowledge. / Lee, Taesung; Hwang, Seung Won; Wang, Zhongyuan.
Proceedings of the 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2016. ed. / Ravi Kumar; James Caverlee; Hanghang Tong. Institute of Electrical and Electronics Engineers Inc., 2016. p. 1392-1393 7752427 (Proceedings of the 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2016).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - Trivia quiz mining using probabilistic knowledge

AU - Lee, Taesung

AU - Hwang, Seung Won

AU - Wang, Zhongyuan

N1 - Funding Information: This work was supported by a grant of the Institute for Information and Communications Technology Promotion (IITP) funded by the Korea government (MSIP) (No. 10041244, SmartTV 2.0 Software Platform) Publisher Copyright: © 2016 IEEE.

PY - 2016/11/21

Y1 - 2016/11/21

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=85006802732&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85006802732&partnerID=8YFLogxK

U2 - 10.1109/ASONAM.2016.7752427

DO - 10.1109/ASONAM.2016.7752427

M3 - Conference contribution

AN - SCOPUS:85006802732

T3 - Proceedings of the 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2016

SP - 1392

EP - 1393

BT - Proceedings of the 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2016

A2 - Kumar, Ravi

A2 - Caverlee, James

A2 - Tong, Hanghang

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2016

Y2 - 18 August 2016 through 21 August 2016

ER -

Lee T, Hwang SW, Wang Z. Trivia quiz mining using probabilistic knowledge. In Kumar R, Caverlee J, Tong H, editors, Proceedings of the 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2016. Institute of Electrical and Electronics Engineers Inc. 2016. p. 1392-1393. 7752427. (Proceedings of the 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2016). doi: 10.1109/ASONAM.2016.7752427

Trivia quiz mining using probabilistic knowledge

Abstract

Publication series

Other

Bibliographical note

All Science Journal Classification (ASJC) codes

Access to Document

Other files and links

Fingerprint

Cite this