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

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.