@inproceedings{fdd6a8eaee974c33ad85b781a1b9956c,
title = "Leveraging aggregate ratings for improving predictive performance of recommender systems",
abstract = "One of the key problems in recommender systems is accurate estimation of unknown ratings of individual items for individual users in terms of the previously specified ratings and other characteristics of items and users. In this thesis, we investigate a way of improving estimations of individual ratings using externally provided properties of aggregate ratings for groups of items and users, such as an externally specified average rating of action movies provided by graduate students or externally specified standard deviation of ratings for comedy movies.",
keywords = "Aggregate ratings, Collaborative filtering, Hierarchical models, Predictive models, Recommender systems",
author = "Akhmed Umyarov",
year = "2008",
doi = "10.1145/1454008.1454064",
language = "English (US)",
isbn = "9781605580937",
series = "RecSys'08: Proceedings of the 2008 ACM Conference on Recommender Systems",
pages = "327--330",
booktitle = "RecSys'08",
note = "2008 2nd ACM International Conference on Recommender Systems, RecSys'08 ; Conference date: 23-10-2008 Through 25-10-2008",
}