Parallel Analysis of Aspect-Based Sentiment Summarization from Online Big-Data
Description:
Consumer's opinions and sentiments on products can reflect the performance of products in general or in various aspects. Analyzing these data is becoming feasible, considering the availability of immense data and the power of natural language processing. However, retailers have not taken full advantage of online comments. This work is dedicated to a solution for automatically analyzing and summarizing these valuable data at both product and category levels. In this research, a system was develo…
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Date:
May 2019
Creator:
Wei, Jinliang
Partner:
UNT Libraries