{"title":"使用深度学习的多模态情感分析","authors":"Rakhee Sharma, Ngoc Tan, F. Sadat","doi":"10.1109/ICMLA.2018.00240","DOIUrl":null,"url":null,"abstract":"Since about a decade ago, deep learning has emerged as a powerful machine learning technique and produced state-of-the-art results in many application domains, ranging from computer vision and speech recognition to NLP. Applying deep learning to sentiment analysis has also become very popular recently. In this paper, we propose a comparative study for multimodal sentiment analysis using deep neural networks involving visual recognition and natural language processing. Initially we make different models for the model using text and another for image and see the results on various models and compare them.","PeriodicalId":6533,"journal":{"name":"2018 17th IEEE International Conference on Machine Learning and Applications (ICMLA)","volume":"16 1","pages":"1475-1478"},"PeriodicalIF":0.0000,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Multimodal Sentiment Analysis Using Deep Learning\",\"authors\":\"Rakhee Sharma, Ngoc Tan, F. Sadat\",\"doi\":\"10.1109/ICMLA.2018.00240\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Since about a decade ago, deep learning has emerged as a powerful machine learning technique and produced state-of-the-art results in many application domains, ranging from computer vision and speech recognition to NLP. Applying deep learning to sentiment analysis has also become very popular recently. In this paper, we propose a comparative study for multimodal sentiment analysis using deep neural networks involving visual recognition and natural language processing. Initially we make different models for the model using text and another for image and see the results on various models and compare them.\",\"PeriodicalId\":6533,\"journal\":{\"name\":\"2018 17th IEEE International Conference on Machine Learning and Applications (ICMLA)\",\"volume\":\"16 1\",\"pages\":\"1475-1478\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 17th IEEE International Conference on Machine Learning and Applications (ICMLA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICMLA.2018.00240\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 17th IEEE International Conference on Machine Learning and Applications (ICMLA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICMLA.2018.00240","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Since about a decade ago, deep learning has emerged as a powerful machine learning technique and produced state-of-the-art results in many application domains, ranging from computer vision and speech recognition to NLP. Applying deep learning to sentiment analysis has also become very popular recently. In this paper, we propose a comparative study for multimodal sentiment analysis using deep neural networks involving visual recognition and natural language processing. Initially we make different models for the model using text and another for image and see the results on various models and compare them.