Estimating the Value of Multi-Dimensional Data Sets in Context-based Recommender Systems.
Panagiotis AdamopoulosAlexander TuzhilinPublished in: RecSys Posters (2014)
Keyphrases
- multi dimensional
- recommender systems
- data sets
- high dimensional data sets
- dimensional data
- collaborative filtering
- index structure
- multi dimensional data
- synthetic data
- matrix factorization
- range queries
- user profiling
- information filtering
- real world
- training set
- real world data sets
- rigid body
- information overload
- cold start problem
- user preferences
- multiple dimensions
- training data
- data streams
- data sparsity
- compound critiques
- product recommendation
- user modeling
- benchmark data sets
- data cube
- user profiles
- input data
- data structure
- information retrieval
- data mining