کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
406121 678064 2016 10 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Fusing audio, visual and textual clues for sentiment analysis from multimodal content
ترجمه فارسی عنوان
سر و صدای صوتی، بصری و متنی برای تحلیل احساسات از محتوای چندجملهای
کلمات کلیدی
تلفیق چندجملهای، تجزیه و تحلیل داده های اجتماعی بزرگ، نظر معادن، تجزیه و تحلیل احساسات چند متغیره، محاسبات سنتی
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر هوش مصنوعی
چکیده انگلیسی

A huge number of videos are posted every day on social media platforms such as Facebook and YouTube. This makes the Internet an unlimited source of information. In the coming decades, coping with such information and mining useful knowledge from it will be an increasingly difficult task. In this paper, we propose a novel methodology for multimodal sentiment analysis, which consists in harvesting sentiments from Web videos by demonstrating a model that uses audio, visual and textual modalities as sources of information. We used both feature- and decision-level fusion methods to merge affective information extracted from multiple modalities. A thorough comparison with existing works in this area is carried out throughout the paper, which demonstrates the novelty of our approach. Preliminary comparative experiments with the YouTube dataset show that the proposed multimodal system achieves an accuracy of nearly 80%, outperforming all state-of-the-art systems by more than 20%.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Neurocomputing - Volume 174, Part A, 22 January 2016, Pages 50–59
نویسندگان
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