文章基本信息

标题：EVALUATING PERFORMANCE OF REVIEW SYSTEM BASED ON KERNEL BASED RELEVANCE VECTOR CLASSIFIER TECHNIQUE
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作者：B.Dhanalakshmi ; A.Chandrasekar
期刊名称：Indian Journal of Computer Science and Engineering
印刷版ISSN：2231-3850
电子版ISSN：0976-5166
出版年度：2017
卷号：8
期号：2
页码：114-118
出版社：Engg Journals Publications
摘要：Generally, a product may have a number of aspects. Some aspects are more important than theothers, and have a greater effect on the repeated consumers’ decision making. A product aspect basedranking framework using kernel based relevance vector classifier technique, which automaticallyidentifies the important aspects of products from online consumers’ reviews. When the consumer wantsto buy a product, ranking of the aspects for the products are done based on the reviews provided by theconsumers in product related sites. A discriminative classifier technique with supervised learning is usedto analyze the online reviews from consumers about hotels. Graphical output will be provided to theconsumer considering positives and negatives of product aspects. A separate graph will be provided foraspects that exist in both positive and negative. Thus, consumers can use this aspect based ranking systemto buy the best product considering all the aspects.
关键词：Relevance vector classifier; Supervised learning; Aspect based Ranking.