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2015 | OriginalPaper | Chapter

Interactive Gender Inference in Social Media

Authors : Zhu Zhu, Jingjing Wang, Shoushan Li, Guodong Zhou

Published in: Database Systems for Advanced Applications

Publisher: Springer International Publishing

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Abstract

In this paper, we define a novel task named interactive gender inference, which aims to utilize interactive text to identify the genders of two interactive users. To address this task, we propose a two stage approach by well incorporating the dependency among the interactive samples sharing identical users. Specifically, we first apply a standard four-category classification algorithm to get a preliminary result, and then propose a global optimization algorithm to achieve better performance. Evaluation demonstrates the effectiveness of our proposed approach to interactive gender inference.

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previous chapter Leveraging Interactive Knowledge and Unlabeled Data in Gender Classification with Co-training
next chapter Joint Sentiment and Emotion Classification with Integer Linear Programming
Literature
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Metadata
Title
Interactive Gender Inference in Social Media
Authors
Zhu Zhu
Jingjing Wang
Shoushan Li
Guodong Zhou
Copyright Year
2015
Book
Database Systems for Advanced Applications

Print ISBN: 978-3-319-22323-0

Electronic ISBN: 978-3-319-22324-7

Copyright Year: 2015

DOI
https://doi.org/10.1007/978-3-319-22324-7_24

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