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:2019,28(9):180-184
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基于在线评论获取产品优化辅助决策信息的算法研究
(宁波大学 机械工程与力学学院, 宁波 315211)
Online Comments Based Algorithm Research for Obtaining Product Optimization Assistant Decision Information
(School of Mechanical Engineering and Mechanics, Ningbo University, Ningbo 315211, China)
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投稿时间:2019-03-03    修订日期:2019-03-24
中文摘要: 在大数据时代,如何通过数据分析抓住顾客需求,增加产品优化的科学性,对企业有着至关重要的战略意义.本文将在线评论数据应用于企业产品的辅助优化中,提出了产品优化信息的获取技术与方法,从评论中获取产品优化所需要的优化信息.首先计算在线评论中的顾客关注度和满意度等指标,构建客户意见的权重算法模型;然后,提取出产品特征和顾客意见的词对,并根据权重算法模型计算出顾客意见的权重;接着,通过关联矩阵找到对应的产品优化信息;最后并通过实例分析验证的方法的可行性.
Abstract:In the era of big data, how to grasp customer needs through data analysis and increase the scientific nature of product optimization is of strategic importance to enterprises. This study applies online comment data to the assisted optimization of enterprise products, proposes techniques and methods for obtaining product optimization information, and realizes the acquisition of product optimization information. Firstly, we calculate the indicators such as customer attention and satisfaction in online reviews, and construct a weighting algorithm model for customer opinions. Next, the word pairs of product characteristics and customer opinions are extracted, and the weight of customer opinions is calculated according to the weight algorithm model. Then, the corresponding product optimization information is found through the correlation matrix. Finally, the feasibility of the method is verified by an example.
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李想.基于在线评论获取产品优化辅助决策信息的算法研究.计算机系统应用,2019,28(9):180-184
LI Xiang.Online Comments Based Algorithm Research for Obtaining Product Optimization Assistant Decision Information.COMPUTER SYSTEMS APPLICATIONS,2019,28(9):180-184

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