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Item-based Collaborative Filtering for Music Recommender System

Blog post from Zilliz

Post Details
Company
Date Published
Author
Zilliz
Word Count
1,286
Company Posts That Month
2
Language
English
Hacker News Points
-
Post removed?
No
Summary

Wanyin App, an AI-based music sharing community, implemented an item-based collaborative filtering (I2I CF) recommender system to sort out music of interest based on users' previous behavior. The system converts songs into mel-frequency cepstrum (MFC), designs a convolutional neural network (CNN) to extract feature embeddings, and uses Milvus as the feature vector similarity search engine for embedding similarity search. This approach helps in generating music recommendations through embedding similarity search and filtering duplicate songs accurately.

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