Abstract. This study proposes a song recommender system. The architecture is
based on a distributed scalable big data framework. The recommender system
analyzes songs a person listens to most and recommends a list of songs as a
playlist. To realize the system, we use Word2vec algorithm by creating vector
representations of songs. Word2vec algorithm is adapted to Apache Spark big
data framework and run on distributed vector representation of songs to pro-
duce a playlist reflecting a person’s personal tastes. The performance results are
evaluated in terms of hit rates at the end of the paper.
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