Author : Nasrin Shah 1
Date of Publication :13th February 2018
Abstract: This article describes the guidelines we use to analyze our opinions, including comments on text and multimedia (images) and the perception of entities and events. Identification is a subset of confidence analysis, which consists of specifying a comment in a comment, such as a specific review of a product or service, a reviewer, a compliment, or a complaint. We use POS tagging to tag individual words in non-verbal or non-verbal terms. We also developed a set of linguistic forms for the same purposes and integrated them into the classifier. The traditional approach we take is a rule-based approach, which we consider subset, taking into account problems that exist in the social colony, such as noisy syntax or misspellings, oaths, or patterns. Other words of scepticism, and so on. The multimedia content analysis makes this work perfect for solving ambiguity issues and providing other contextual information. The main task for this: First, the combination of new tools to extract information from text and multimedia; Secondly, the adaptation of the NLP tool for exploring specific information to solve the problem. The classifier combination with the embedded word model for confidence analysis helps our approach to better accuracy than modern methods.
Reference :
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- Quan Fang, Changsheng Xu, Fellow, IEEE, Jitao Sang, M. Shamim Hossain, Senior Member, IEEE, and Ghulam Muhammad, Member, IEEE Word-of-Mouth Understanding: Entity-Centric Multimodal Aspect-Opinion Mining in Social Media
- B. Liu and L. Zhang, ―A survey of opinion mining and sentiment analysis,‖ in Mining Text Data. New York, NY, USA: Springer, 2012, pp. 415–463.
- K. L. Keller, ―Conceptualizing, measuring, and managing customer based brand equity,‖ J. Marketing, vol. 1, no. 1, pp. 1–22, 1993.
- D. Carmel, N. Zwerdling, I. Guy, S. Ofek-Koifman, N. Har’El, I. Ronen, E. Uziel, S. Yogev, and S. Chernov, ―Personalized social search based on the user’s social network,‖ in Proc.CIKM, 2009, pp. 1227–1236.
- M. Hu and B. Liu, ―Mining and summarizing customer reviews,‖ in Proc. KDD, 2004, pp. 168–177.
- S. Moghaddam and M. Ester, ―On the design of lda models for aspectbased opinion mining,‖ in Proc. CIKM, 2012, pp. 803–812.