The perfumes have text descriptions, reviews, and a list of notes. I now have two documents I can use to find similar perfumes. I highly recommend trying it out if you have a project where you’d like to use sentiment analysis.) I concatenate all positive and neutral sentences into one string, and all negative sentiment sentences into another string. (It was super easy to use, and gave me great results. The first step in the model is to identify the sentiment of each sentence from the chatbot message. The fourth perfume disappears from the recommendations! The Model Here is an example of all three text data sources for my personal favorite perfume, Delma. I scraped three sources of text data and concatenated these into one document per perfume: I wrote a python script to scrape data from a popular niche perfume website.
![perfume suggester perfume suggester](https://sabishops.com/wp-content/uploads/2021/02/181383220_181391230_1_2_720x928.jpg)
I want to be able to describe what I don’t like as well as what I do like, and still receive relevant recommendations. Because of the modeling approach used, and because the language of perfume is so rich, this model can recommend perfumes that match a description of a mood, a feeling, a personality, or an event like a vacation
![perfume suggester perfume suggester](https://milanomodelsfactory.com/wp-content/uploads/2020/11/18S4.jpg)
As a perfume lover and a Data Scientist, the unusual and highly descriptive language used in the niche perfume community inspired me to use NLP to create a model to help me discover perfumes I might want to purchase. Natural Language Processing(NLP) has many intriguing applications to Recommender Systems and Information Retrieval.
![perfume suggester perfume suggester](https://thefreebieguy.com/wp-content/uploads/2020/09/MFSF-1024x538.png)
Your own personal AI chatbot will reply and will help you discover personalized perfume recommendations.) (If you’d like to try out this model, you can text the live bot by texting “Hi” to (424)343–3755 to get started. Photo by Jessica Weiller on Unsplash Introduction