Latent Class Analysis (LCA) Based Approach for Finding Best Hotels

被引：1

作者：

Singh, Vijay ^{[1
]}

Pant, Bhasker ^{[1
]}

Singh, D. P. ^{[1
]}

Kumar, Santosh ^{[1
]}

机构：

[1] Graph Era Deemed Univ, Dehra Dun 248002, India

来源：

COMPUTING, COMMUNICATION AND SIGNAL PROCESSING, ICCASP 2018 | 2019年 / 810卷

关键词：

Latent Class Analysis (LCA); Statistical modeling; Trip advisor;

D O I：

10.1007/978-981-13-1513-8_22

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Researchers shows a huge interest in Latent Class Analysis (LCA) in various domains over the last two decades. We proposed a new Latent Class Data Analysis using Statistical modeling approach to categorize better and worst Hotel to Stay. The main objective of this study was to find the unobserved classes in the Trap Advisor dataset. The results allow to identify new entry of the Hotel and detects whether it lies in Good Hotel category or in worst Hotel category. For evaluation and demonstration purpose freely, available Trip Advisor dataset is used.

引用

页码：205 / 213

页数：9

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