作者
Soujanya Poria, Iti Chaturvedi, Erik Cambria, Amir Hussain
发表日期
2016/12/12
研讨会论文
2016 IEEE 16th international conference on data mining (ICDM)
页码范围
439-448
出版商
IEEE
简介
Technology has enabled anyone with an Internet connection to easily create and share their ideas, opinions and content with millions of other people around the world. Much of the content being posted and consumed online is multimodal. With billions of phones, tablets and PCs shipping today with built-in cameras and a host of new video-equipped wearables like Google Glass on the horizon, the amount of video on the Internet will only continue to increase. It has become increasingly difficult for researchers to keep up with this deluge of multimodal content, let alone organize or make sense of it. Mining useful knowledge from video is a critical need that will grow exponentially, in pace with the global growth of content. This is particularly important in sentiment analysis, as both service and product reviews are gradually shifting from unimodal to multimodal. We present a novel method to extract features from visual …
引用总数
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S Poria, I Chaturvedi, E Cambria, A Hussain - 2016 IEEE 16th international conference on data …, 2016