A Sentiment analysis-based hotel recommendation using TF-IDF Approach

被引：0

作者：

Mishra, Ram Krishn ^{[1
]}

Urolagin, Siddhaling ^{[1
]}

Jothi, Angel Arul J. ^{[1
]}

机构：

[1] BITS Pilani, Dept Comp Sci, Dubai Campus, Dubai, U Arab Emirates

来源：

PROCEEDINGS OF 2019 INTERNATIONAL CONFERENCE ON COMPUTATIONAL INTELLIGENCE AND KNOWLEDGE ECONOMY (ICCIKE' 2019) | 2019年

关键词：

Recommendation Systems; TF-IDF; Sentiment Analysis;

D O I：

10.1109/iccike47802.2019.9004385

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Speedy evolution in the internet world has enforced many users to use internet services for daily basis work. Tourism industry has played a vital role for internet users by offering economical and comparable prices for hotel booking. In current scenario it has been observed that many users share their views by giving their feedback in different forms like blogs, web forums, social media etc. In this research we have used term frequency-inverse document frequency(TF-IDF) and Cosine Similarity to provide more options of hotels based on their reviews. TF-IDF helps to find the weight value of terms or documents frequency and the cosine similarity helps to extract similar kinds of values from the sentiment dataset.

引用

页码：811 / 815

页数：5

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