Scalable Image Sentiment Analysis Engine

DigitalMR建议研究大规模视觉情绪分析系统的可行性。该项目的关键目标是构建一个高性能的情感分析引擎，该引擎应用中层表示来弥合语义概念和情感/情感感知之间的差距。高级营销高管对这类系统的需求越来越大，他们想方设法包括越来越多的与形象相关的帖子，这些帖子约占所有推文的三分之一。该项目与竞赛的数据探索部分保持一致，特别是副主题：a)自动化和智能的数据清理和语义注释，以及b)从复杂数据集中提取价值和洞察力的新算法和方法。

DigitalMR proposes to investigate the feasibility of a large scale visual sentiment analysis system. The key goal of the project is to construct a high performance sentiment analysis engine that applies a mid-level representation to bridge the gap between semantic concepts and sentiment/emotion perception. Such systems are increasingly in demand by senior marketing executives who look for ways to include the growing number of image relates posts which account for around a third of all tweets. The project is aligned with the data exploration part of the competition and and in particular the subtopics: a) automated & intelligent data cleansing & semantic annotation and b) new algorithms and approaches to extract value and insight from complex data sets.