---
title: "Interactive Gender Inference with Integer Linear Programming"
authors:
  - "Shoushan Li"
  - "Jingjing Wang"
  - "Guodong Zhou"
  - "Hanxiao Shi"
doi: ""
url: "https://ijcai.org/proceedings/2015/331"
pdf: "https://ijcai.org/proceedings/2015/0331.pdf"
venue: "Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence"
year: 2015
pages: "2341-2346"
track: "Main Track"
keywords:
---

# Interactive Gender Inference with Integer Linear Programming

Shoushan Li, Jingjing Wang, Guodong Zhou, Hanxiao Shi

*Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence*, pages 2341-2346.

## Abstract

Interactive gender inference aims to infer the genders of the two involved users in a communication from the interactive text. In this paper, we address this task by proposing a joint inference approach which well incorporates label correlations among the instances. Specifically, an Integer Linear Programming (ILP) approach is proposed to achieve global optimization with various kinds of intra-task and extra-task constraints. Empirical studies demonstrate the effectiveness of the proposed ILP-based approach to interactive gender inference.