Weighted Co-Training for Cross-Domain Image SentimentClassification  

作　　者：Meng Chen Lin-Lin Zhang Xiaohui Yu Yang Liu 

机构地区：[1]School of Computer Science and Technology, Shandong University, Jinan 250101, China [2]School of Information Technology, York University, Toronto, M3J 1P3, Canada

出　　处：《Journal of Computer Science & Technology》2017年第4期714-725,共12页计算机科学技术学报（英文版）

摘　　要：Image sentiment classification, which aims to predict the polarities of sentiments conveyed by the images, has gained a lot of attention. Most existing methods address this problem by training a general classifier with certain visual features, ignoring the discrepancies across domains. In this paper, we propose a novel weighted co-training method for cross-domain image sentiment classification, which iteratively enlarges the labeled set by introducing new high-confidence classified samples to reduce the gap between the two domains. We train two sentiment classifiers with both the images and the corresponding textual comments separately, and set the similarity between the source domain and the target domain as the weight of a classifier. We perform extensive experiments on a real Flickr dataset to evaluate the proposed method, and the empirical study reveals that the weighted co-training method significantly outperforms some baseline solutions.Image sentiment classification, which aims to predict the polarities of sentiments conveyed by the images, has gained a lot of attention. Most existing methods address this problem by training a general classifier with certain visual features, ignoring the discrepancies across domains. In this paper, we propose a novel weighted co-training method for cross-domain image sentiment classification, which iteratively enlarges the labeled set by introducing new high-confidence classified samples to reduce the gap between the two domains. We train two sentiment classifiers with both the images and the corresponding textual comments separately, and set the similarity between the source domain and the target domain as the weight of a classifier. We perform extensive experiments on a real Flickr dataset to evaluate the proposed method, and the empirical study reveals that the weighted co-training method significantly outperforms some baseline solutions.

关 键 词：sentiment classification cross-domain weighted co-training 

分 类 号：TP[自动化与计算机技术]