Evolution and Quality Analysis Algorithm of Consumer Online Reviews Based on Data Fusion and Multiobjective Optimization

With the rise of network strategies, various businesses using the Internet as a platform have been vigorously developed, among which the scale of e-commerce transactions has increased on a large scale. In order to deeply explore the role and advantages of data fusion and multiobjective optimization...

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Autores principales:	Hu Wang, Tianbao Liang, Yanxia Cheng
Formato:	article
Lenguaje:	EN
Publicado:	Hindawi Limited 2021
Materias:	Technology (General) T1-995
Acceso en línea:	https://doaj.org/article/49edd65b54f74ba093d2e32d02b30903
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spelling	oai:doaj.org-article:49edd65b54f74ba093d2e32d02b309032021-11-15T01:19:31ZEvolution and Quality Analysis Algorithm of Consumer Online Reviews Based on Data Fusion and Multiobjective Optimization1687-726810.1155/2021/6252425https://doaj.org/article/49edd65b54f74ba093d2e32d02b309032021-01-01T00:00:00Zhttp://dx.doi.org/10.1155/2021/6252425https://doaj.org/toc/1687-7268With the rise of network strategies, various businesses using the Internet as a platform have been vigorously developed, among which the scale of e-commerce transactions has increased on a large scale. In order to deeply explore the role and advantages of data fusion and multiobjective optimization technology in consumer online reviews, this paper uses the new and old evaluation model comparison method, algorithm design method, and multiobject research method to collect samples, analyze the technical model, and streamline the algorithm. And it will create an analysis algorithm model that can improve and optimize the consumer’s current online reviews. First, we choose the electricity supplier on the platform of a total of four mobile phones grabbed 32,145 comments. Based on this research on the number of online comment fields of consumers, the results show that 78% of the comments are less than 55 words, indicating that most of the online comments left by consumers are short comments; at the same time, a small number of consumers have left detailed comments. Description, the longest of is reached 612 words. On this basis, further study the efficiency and function analysis of the algorithm proposed in this paper, and we can see that DCDG-MOMA is used in 14-7 and 28-7 use cases as 1 and 2, respectively, which is the least, and at 40-7 and 50-7, the time used is 15 and 20 which is close to PBI, but it is also much less time than the MOMAD algorithm. This further shows that the algorithm really plays an effective role in the actual decision-making process. It has basically realized a more efficient algorithm for consumer online reviews under the background of applying data fusion and multiobjective optimization technology.Hu WangTianbao LiangYanxia ChengHindawi LimitedarticleTechnology (General)T1-995ENJournal of Sensors, Vol 2021 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Technology (General) T1-995
spellingShingle	Technology (General) T1-995 Hu Wang Tianbao Liang Yanxia Cheng Evolution and Quality Analysis Algorithm of Consumer Online Reviews Based on Data Fusion and Multiobjective Optimization
description	With the rise of network strategies, various businesses using the Internet as a platform have been vigorously developed, among which the scale of e-commerce transactions has increased on a large scale. In order to deeply explore the role and advantages of data fusion and multiobjective optimization technology in consumer online reviews, this paper uses the new and old evaluation model comparison method, algorithm design method, and multiobject research method to collect samples, analyze the technical model, and streamline the algorithm. And it will create an analysis algorithm model that can improve and optimize the consumer’s current online reviews. First, we choose the electricity supplier on the platform of a total of four mobile phones grabbed 32,145 comments. Based on this research on the number of online comment fields of consumers, the results show that 78% of the comments are less than 55 words, indicating that most of the online comments left by consumers are short comments; at the same time, a small number of consumers have left detailed comments. Description, the longest of is reached 612 words. On this basis, further study the efficiency and function analysis of the algorithm proposed in this paper, and we can see that DCDG-MOMA is used in 14-7 and 28-7 use cases as 1 and 2, respectively, which is the least, and at 40-7 and 50-7, the time used is 15 and 20 which is close to PBI, but it is also much less time than the MOMAD algorithm. This further shows that the algorithm really plays an effective role in the actual decision-making process. It has basically realized a more efficient algorithm for consumer online reviews under the background of applying data fusion and multiobjective optimization technology.
format	article
author	Hu Wang Tianbao Liang Yanxia Cheng
author_facet	Hu Wang Tianbao Liang Yanxia Cheng
author_sort	Hu Wang
title	Evolution and Quality Analysis Algorithm of Consumer Online Reviews Based on Data Fusion and Multiobjective Optimization
title_short	Evolution and Quality Analysis Algorithm of Consumer Online Reviews Based on Data Fusion and Multiobjective Optimization
title_full	Evolution and Quality Analysis Algorithm of Consumer Online Reviews Based on Data Fusion and Multiobjective Optimization
title_fullStr	Evolution and Quality Analysis Algorithm of Consumer Online Reviews Based on Data Fusion and Multiobjective Optimization
title_full_unstemmed	Evolution and Quality Analysis Algorithm of Consumer Online Reviews Based on Data Fusion and Multiobjective Optimization
title_sort	evolution and quality analysis algorithm of consumer online reviews based on data fusion and multiobjective optimization
publisher	Hindawi Limited
publishDate	2021
url	https://doaj.org/article/49edd65b54f74ba093d2e32d02b30903
work_keys_str_mv	AT huwang evolutionandqualityanalysisalgorithmofconsumeronlinereviewsbasedondatafusionandmultiobjectiveoptimization AT tianbaoliang evolutionandqualityanalysisalgorithmofconsumeronlinereviewsbasedondatafusionandmultiobjectiveoptimization AT yanxiacheng evolutionandqualityanalysisalgorithmofconsumeronlinereviewsbasedondatafusionandmultiobjectiveoptimization
_version_	1718428919733944320

Evolution and Quality Analysis Algorithm of Consumer Online Reviews Based on Data Fusion and Multiobjective Optimization

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