Data
LastFM_dataset

LastFM_dataset

active ARFF Publicly available Visibility: public Uploaded 08-09-2022 by Giulio Filippi
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Last FM Dataset ------- Version ------- Version 1.0 (May 2011) ----------- Description ----------- This dataset contains social networking, tagging, and music artist listening information from a set of 2K users from Last.fm online music system. http://www.last.fm The dataset is released in the framework of the 2nd International Workshop on Information Heterogeneity and Fusion in Recommender Systems (HetRec 2011) http://ir.ii.uam.es/hetrec2011 at the 5th ACM Conference on Recommender Systems (RecSys 2011) http://recsys.acm.org/2011 ------- License ------- The users' names and other personal information in Last.fm are not provided in the dataset. The data contained in hetrec2011-lastfm-2k.zip is made available for non-commercial use. Those interested in using the data in a commercial context should contact Last.fm staff: http://www.lastfm.com/about/contact ---------------- Acknowledgements ---------------- This work was supported by the Spanish Ministry of Science and Innovation (TIN2008-06566-C04-02), and the Regional Government of Madrid (S2009TIC-1542). ---------- References ---------- When using this dataset you should cite: - Last.fm website, http://www.lastfm.com You may also cite HetRec'11 workshop as follows: @inproceedings{Cantador:RecSys2011, author = {Cantador, Iv\'{a}n and Brusilovsky, Peter and Kuflik, Tsvi}, title = {2nd Workshop on Information Heterogeneity and Fusion in Recommender Systems (HetRec 2011)}, booktitle = {Proceedings of the 5th ACM conference on Recommender systems}, series = {RecSys 2011}, year = {2011}, location = {Chicago, IL, USA}, publisher = {ACM}, address = {New York, NY, USA}, keywords = {information heterogeneity, information integration, recommender systems}, }

4 features

usernumeric15000 unique values
0 missing
artiststring1004 unique values
0 missing
sexstring2 unique values
0 missing
countrystring159 unique values
0 missing

19 properties

289955
Number of instances (rows) of the dataset.
4
Number of attributes (columns) of the dataset.
Number of distinct values of the target attribute (if it is nominal).
0
Number of missing values in the dataset.
0
Number of instances with at least one value missing.
1
Number of numeric attributes.
0
Number of nominal attributes.
0
Percentage of binary attributes.
0
Percentage of instances having missing values.
0
Percentage of missing values.
Average class difference between consecutive instances.
25
Percentage of numeric attributes.
0
Number of attributes divided by the number of instances.
0
Percentage of nominal attributes.
Percentage of instances belonging to the most frequent class.
Number of instances belonging to the most frequent class.
Percentage of instances belonging to the least frequent class.
Number of instances belonging to the least frequent class.
0
Number of binary attributes.

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