SCIENCE@home

MongoDB Clustering using K-means for Real-Time Song Recognition

M. A. Sahbudin,Marco Scarpa,Salvatore Serrano

Published 2019 in International Conference on Computing, Networking and Communications

ABSTRACT

Recently, the increased competition in song recognition has led to the necessity to identify songs within very huge databases compared to previous years. Therefore, information retrieval technique requires a more efficient and scalable data storage framework. In this work, we propose an approach exploiting K-means clustering and describe strategies for improving accuracy and speed. In collaboration with an audio expert company providing us with 2.4 billion fingerprints data, we evaluated the performance of the proposed clustering and recognition algorithm.

PUBLICATION RECORD

  • Publication year

    2019

  • Venue

    International Conference on Computing, Networking and Communications

  • Publication date

    2019-02-01

  • Fields of study

    Computer Science

  • Identifiers
    DOI 10.1109/ICCNC.2019.8685489
  • External record

    Open on Semantic Scholar

  • Source metadata

    Semantic Scholar

CITATION MAP

EXTRACTION MAP

CLAIMS

  • No claims are published for this paper.

CONCEPTS

  • No concepts are published for this paper.

REFERENCES

Showing 1-8 of 8 references · Page 1 of 1

CITED BY