/plushcap/analysis/zilliz/music-recommender-system-item-based-collaborative-filtering-milvus

Item-based Collaborative Filtering for Music Recommender System

What's this blog post about?

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.

Company
Zilliz

Date published
Sept. 7, 2020

Author(s)
Zilliz

Word count
1286

Language
English

Hacker News points
None found.


By Matt Makai. 2021-2024.