Re-Ranking Voting-Based Answers by Discarding User Behavior Biases
Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence. Main Track. Pages 2380-2385.
Abstract
The vote mechanism is widely utilized to rank answers in community-based question answering sites. In generating a vote, a user's attention is influenced by the answer position and appearance, in addition to real answer quality. Previously, these biases are ignored. As a result, the top answers obtained from this mechanism are not reliable, if the number of votes for the active question is not sufficient. In this paper, we solve this problem by analyzing two kinds of biases; position bias and appearance bias. We identify the existence of these biases and propose a joint click model for dealing with both of them. Our experiments in real data demonstrate how the ranking performance of the proposed model outperforms traditional methods with biases ignored by 15.1% in precision@1, and 11.7% in the mean reciprocal rank. A case study on a manually labeled dataset futher supports the effectiveness of the proposed model.
@inproceedings{ijcai2015p337,
title = {Re-Ranking Voting-Based Answers by Discarding User Behavior Biases},
author = {Wei, Xiaochi and Huang, Heyan and Lin, Chin-Yew and Xin, Xin and Mao, Xianling and Wang, Shangguang},
booktitle = {Proceedings of the Twenty-Fourth International Joint Conference on
Artificial Intelligence, {IJCAI-15}},
publisher = {International Joint Conferences on Artificial Intelligence},
editor = {Qiang Yang and Michael Wooldridge},
pages = {2380--2385},
year = {2015},
month = {7},
note = {Main Track},
url = {https://ijcai.org/proceedings/2015/337},
}
TY - CPAPER TI - Re-Ranking Voting-Based Answers by Discarding User Behavior Biases AU - Wei, Xiaochi AU - Huang, Heyan AU - Lin, Chin-Yew AU - Xin, Xin AU - Mao, Xianling AU - Wang, Shangguang T2 - Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, IJCAI-15 PB - International Joint Conferences on Artificial Intelligence PY - 2015 SP - 2380 EP - 2385 UR - https://ijcai.org/proceedings/2015/337 ER -Copied
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