A General Gender Inference Method Based on Web

DOI

10.2991/aiie-16.2016.49How to use a DOI?

Keywords

component; data mining; gender prediction; demographic; big data

Abstract

Gender information, as a crucial part of human demographics, is valuable for its abundant connotations and potential applications. Though much effort has been made on the problem of gender inference, most existing methods are highly dependent on data from specific sources, like Twitter, and are difficult to be generalized to other tasks. In this work, we propose a general Web-based method for gender inference. We show that our model significantly outperforms state-of-the-art without much human workload or any limits on specific scenarios. Based on that, we also present a voting framework to efficiently incorporate several methods to further improve performance. Experiments show that our voting framework can achieve 96.9% accuracy.

Copyright

© 2016, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Hong Yang
AU  - Yali Yuan
PY  - 2016/11
DA  - 2016/11
TI  - A General Gender Inference Method Based on Web
BT  - Proceedings of the 2016 2nd International Conference on Artificial Intelligence and Industrial Engineering (AIIE 2016)
PB  - Atlantis Press
SP  - 210
EP  - 213
SN  - 1951-6851
UR  - https://doi.org/10.2991/aiie-16.2016.49
DO  - 10.2991/aiie-16.2016.49
ID  - Yang2016/11
ER  -