IEEE Style Citation: Karishma Mandloi, Amit Mittal, “Hybrid Music Recommendation System Using Content-based Filtering and K-Mean Clustering Algorithm,” International Journal of Computer Sciences and Engineering, Vol.6, Issue.7, pp.1498-1501, 2018.
MLA Style Citation: Karishma Mandloi, Amit Mittal "Hybrid Music Recommendation System Using Content-based Filtering and K-Mean Clustering Algorithm." International Journal of Computer Sciences and Engineering 6.7 (2018): 1498-1501.
APA Style Citation: Karishma Mandloi, Amit Mittal, (2018). Hybrid Music Recommendation System Using Content-based Filtering and K-Mean Clustering Algorithm. International Journal of Computer Sciences and Engineering, 6(7), 1498-1501.
BibTex Style Citation:
@article{Mandloi_2018,
author = {Karishma Mandloi, Amit Mittal},
title = {Hybrid Music Recommendation System Using Content-based Filtering and K-Mean Clustering Algorithm},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {7 2018},
volume = {6},
Issue = {7},
month = {7},
year = {2018},
issn = {2347-2693},
pages = {1498-1501},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=2632},
doi = {https://doi.org/10.26438/ijcse/v6i7.14981501}
publisher = {IJCSE, Indore, INDIA},
}
RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v6i7.14981501}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=2632
TI - Hybrid Music Recommendation System Using Content-based Filtering and K-Mean Clustering Algorithm
T2 - International Journal of Computer Sciences and Engineering
AU - Karishma Mandloi, Amit Mittal
PY - 2018
DA - 2018/07/31
PB - IJCSE, Indore, INDIA
SP - 1498-1501
IS - 7
VL - 6
SN - 2347-2693
ER -
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Abstract
Data is recognized as an important source for knowledge generation. Sometime user may aware about requirement but sometime may not. Recommender systems are software or technical facilities to provide items suggestions or predict customer preferences by using prior user information. Recommendations can help to increase sales and improve user satisfaction. Music Recommendation system can help to explore relative music based on user preference or internal similarity. A hybrid recommender system is usually developed through the combination of multiple recommendation techniques to boost the quality of recommendations. This paper uses content-based filtering with K-mean clustering algorithm for music recommendation system which provides effective and relevant content to be suggested.
Key-Words / Index Term
Recommendation system; Content-based filtering; K-mean; Data Mining
References
[1]. Paulo Chiliguano, Gyorgy Fazekas “Hybrid Music Recommender Using Content-based And Social Information” published in IEEE ICASSP, 2016 pp 2618-2622
[2]. Milind Mathur, Ayush Kesarwani , “Selective Unsupervised Feature Learning with Convolutional Neural Network (S-CNN)” published in NCNHIT 2013
[3]. B Amini, R Ibrahim, MS Othman, MA Nematbakhsh . Expert Systems with Applications 42 (2), 913-928, 2015 . 14, 2015. Discovering the impact of knowledge in recommender systems: A comparative study International Journal of Computer Applications (0975–8887) 23 (4).
[4]. Jyotsna Chanda, “An Improved Web Page Recommendation System Using Partitioning and Web Usage Mining” Proceedings of the International Conference on Intelligent Processing, Security and Advanced Communication. Article No. 80.
[5]. International Journal of Scientific Research in Computer Sciences and Engineering (ISSN: 2320-7639) .
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