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music-recsys's Introduction

简介

就在几年前,很难想象同一个人会在早上通勤的路上听披头士乐队、维瓦尔第和 Lady Gaga 的音乐。但是,电台 DJ 的辉煌时代已经过去,musical gatekeepers have been replaced with personalizing algorithms and unlimited streaming services.

虽然公众现在在听各种音乐,但算法仍然在关键领域挣扎。如果没有足够的历史数据,算法如何知道听众会喜欢一首新歌还是一位新艺术家?而且,它如何知道向新用户推荐哪些歌曲?

WSDM 向 Kaggle ML 社区发起了挑战,以帮助解决这些问题并构建更好的音乐推荐系统。该数据集来自亚洲领先的音乐流媒体服务 KKBOX,拥有世界上最全面的亚洲流行音乐库,拥有超过 3000 万首曲目。他们目前在他们的推荐系统中使用基于协同过滤的算法,该算法具有矩阵分解和词嵌入,但相信新技术可以带来更好的结果。

Winners will present their findings at the conference February 6-8, 2018 in Los Angeles, CA. For more information on the conference, click here, and don't forget to check out the other KKBox/WSDM competition: KKBox Music Churn Prediction Challenge.

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