I am building a recommendation system for hotel accommodation. I scraped data from online booking portal and now my data has Name of the hotel, review, description and location.

I built a simple content-based recommendation. I combined the hotel name, location and description. Then, used NLP and TF-IDF to convert into vectors. I used cosine similarity for recommending the hotel name.

I have taken a hotel name as an input and model recommends the hotels. I have the following questions,

1) If I wanted to find hotel recommendations based on keywords instead of hotel names, do you have any suggestions on how I can do it? For example, Instead of giving hotel name, can I give the location name or typing IBIS (IBIS Singapore - > is a complete hotel name)

2) Second, I don't have a hotel ID, how to do Collaborative recommendation system with my present dataset?

Please advise


1 Answer 1

  1. Not sure what your production requirements are for your collaborative filtering system, but from a research standpoint, I have had a good experience with the Surprise Package for Python.

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