Judging Similarity: A User-Centric Study of Related Item Recommendations - Dataset

Yao, Yuan
Harper, F Maxwell
2018-08-02
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https://doi.org/10.13020/D67700
 https://hdl.handle.net/11299/198736
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2018-03-21
2018-04-16

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Title

Judging Similarity: A User-Centric Study of Related Item Recommendations - Dataset

Published Date

2018-08-02

Authors

Group

GroupLens Center for Social and Human-Centered Computing
University of Minnesota Department of Computer Science and Engineering

Author Contact

Harper, F Maxwell
max@umn.edu

Type

Dataset
Experimental Data
Survey Data-Qualitative
Survey Data-Quantitative

Abstract

This dataset describes survey results about the similarity of pairs of movies from the MovieLens recommender system. These data are described in the research paper "Judging Similarity: A User-Centric Study of Related Item Recommendations", published in the ACM Conference on Recommender Systems (RecSys), 2018. The data were collected between March 21 and April 16, 2018.

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https://doi.org/10.1145/3240323.3240351

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Attribution 3.0 United States
 http://creativecommons.org/licenses/by/3.0/us/

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Data Repository for U of M (DRUM)

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Amazon
Google

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Suggested citation

Yao, Yuan; Harper, F Maxwell. (2018). Judging Similarity: A User-Centric Study of Related Item Recommendations - Dataset. Retrieved from the Data Repository for the University of Minnesota (DRUM), https://doi.org/10.13020/D67700.

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Description
Size
README.txt
Description of the Data
(5.95 KB)

neighbors.csv
The 1000 "neighbors" generated by each of the six experimental algorithms
(289.47 KB)

pair-responses.csv
Movie similarity and recommendation quality
(1.05 MB)

survey-responses.csv
Survey responses about movie similarity and related item recommendations
(111.24 KB)

test-set.csv
Test set of 100 "seed" movie IDs
(3.11 KB)

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