NDLI: Investigating country-specific music preferences and music recommendation algorithms with the LFM-1b dataset

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Investigating country-specific music preferences and music recommendation algorithms with the LFM-1b dataset

Content Provider	Springer Nature Link
Author	Schedl, Markus
Copyright Year	2017
Abstract	Recently, the LFM-1b dataset has been proposed to foster research and evaluation in music retrieval and music recommender systems, Schedl (Proceedings of the ACM International Conference on Multimedia Retrieval (ICMR). New York, 2016). It contains more than one billion music listening events created by more than 120,000 users of Last.fm. Each listening event is characterized by artist, album, and track name, and further includes a timestamp. Basic demographic information and a selection of more elaborate listener-specific descriptors are included as well, for anonymized users. In this article, we reveal information about LFM-1b’s acquisition and content and we compare it to existing datasets. We furthermore provide an extensive statistical analysis of the dataset, including basic properties of the item sets, demographic coverage, distribution of listening events (e.g., over artists and users), and aspects related to music preference and consumption behavior (e.g., temporal features and mainstreaminess of listeners). Exploiting country information of users and genre tags of artists, we also create taste profiles for populations and determine similar and dissimilar countries in terms of their populations’ music preferences. Finally, we illustrate the dataset’s usage in a simple artist recommendation task, whose results are intended to serve as baseline against which more elaborate techniques can be assessed.
Starting Page	71
Ending Page	84
Page Count	14
File Format	PDF
ISSN	21926611
Journal	International Journal of Multimedia Information Retrieval
Volume Number	6
Issue Number	1
e-ISSN	2192662X
Language	English
Publisher	Springer London
Publisher Date	2017-02-06
Publisher Place	London
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Information Systems Applications (incl.Internet) Music taste analysis Music recommender systems Statistical analysis Dataset Information Storage and Retrieval Data Mining and Knowledge Discovery Image Processing and Computer Vision Computer Science Experimentation Multimedia Information Systems Music information retrieval
Content Type	Text
Resource Type	Article
Subject	Library and Information Sciences Information Systems Media Technology

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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