I am working on building a recommender system and require a work flow for the same. I have user data in .csv files.
Any help regarding the same would be appreciated.
Thank you.
Which recommender system or project you are working on?
- If it is content based like showing the similar products or movies/ books etc based on your items.
Content based
The you can use techniques.
- Euclidean distance to calculate the similarity b/t them and recoomed it.
- cosine similarity
- Jaccard similarity
Similar above techniques will be using the jobs recommendations systems or skills recommendations system if you are working on it.
- You can use the collaborative filtering method.
It checks about the taste of similar users based on their purchase does recommendations.
b) Collaborative Filtering based approach.
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If there is an intersections b/t A and B user then they are similar and (A-B) difference will be recommended to B and (B-A) difference will be recommended to A.
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By using SVD algorithm (Single value matrix factorization also you are find the the two user represented as matrix who are similar.
Refer the below for the project but it is computationally intensive as it is using the SVD algo.