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A weighted sum method MCDM approach for recommending product using sentiment analysis

机译:一种使用情感分析推荐产品的加权和方法MCDM方法

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In recent times, reviews of products by customers have been proliferating on the online platform. Majority of the reviews are lengthy, and going through the reviews before making a decision can be a tedious task for the user. In this paper, we extract the popular features from customers' reviews to analyse the possible opinions of these features. Choosing a product from the different combination of opinions for these features is treated as a multi-criteria decision making (MCDM) problem. Weighted sum method, a MCDM approach, is used to evaluate the priority score for each product. The product with the highest score is recommended to the user. Real-time dataset from Amazon is used to evaluate our system's performance. The experimental result shows that our proposed method produces a promising result which can help the user in the decision making process.
机译:最近,在线平台上,客户的评论是由客户的增强。大多数评论是漫长的,并在做出决定之前通过评论可能是用户的繁琐任务。在本文中,我们从客户评论中提取了流行的功能,以分析这些功能的可能意见。从不同的意见组合选择这些功能的产品被视为多标准决策(MCDM)问题。加权SUM方法是MCDM方法,用于评估每个产品的优先级分数。建议使用具有最高分的产品。亚马逊的实时数据集用于评估我们的系统性能。实验结果表明,我们的提出方法产生了一个有希望的结果,可以帮助用户在决策过程中。

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