A Multiple Classifier System for Classifying Life Events on Social Media

2015 IEEE International Conference on Data Mining Workshop (ICDMW) Pub Date : 2015-11-14 DOI:10.1109/ICDMW.2015.182

P. Cavalin, L. G. Moyano, Pedro P. Miranda

引用次数: 11

Abstract

In this work we present a Conversation Classifierbased on Multiple Classifiers, to detect Life Events on SocialMedia. In one hand, conversations can provide more contextand help disambiguate life event detection, compared with single posts. On the other hand, the increase in number of messages and the way they interact with each other within the conversation cannot be trivially modeled by a classifier. To tackle this problem, we focus on creating a set of classifiers from different feature sets, and combining their classification outputs to improve accuracy. The experiments show that multiple classifiers are promising for this problem, being able to present an increase of about 45% in the F-Score.

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社交媒体生活事件分类的多分类器系统

在这项工作中，我们提出了一个基于多分类器的会话分类器，用于检测社交媒体上的生活事件。一方面，与单个帖子相比，对话可以提供更多的上下文，帮助消除生活事件检测的歧义。另一方面，消息数量的增加以及它们在会话中相互交互的方式不能由分类器简单地建模。为了解决这个问题，我们专注于从不同的特征集创建一组分类器，并结合它们的分类输出来提高准确率。实验表明，对于这个问题，多个分类器是有希望的，能够在F-Score中增加约45%。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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2015 IEEE International Conference on Data Mining Workshop (ICDMW)

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