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

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Collection period

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

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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Referenced by

https://doi.org/10.1145/3240323.3240351

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Amazon
Google

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Previously Published Citation

Suggested citation

Yao, Yuan; Harper, F Maxwell. (2018). Judging Similarity: A User-Centric Study of Related Item Recommendations - Dataset. Retrieved from the University Digital Conservancy, https://doi.org/10.13020/D67700.
View/Download file
File View/OpenDescriptionSize
README.txtDescription of the Data5.95 KB
neighbors.csvThe 1000 "neighbors" generated by each of the six experimental algorithms289.47 KB
pair-responses.csvMovie similarity and recommendation quality1.05 MB
survey-responses.csvSurvey responses about movie similarity and related item recommendations111.24 KB
test-set.csvTest set of 100 "seed" movie IDs3.11 KB

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