Introducing a Star Topology into Latent Class Models for Collaborative Filtering

Latent class models (LCM) represent the high dimensional data in a smaller dimensional space in terms of latent variables. They are able to automatically discover the patterns from the data. We present a topographic version of two LCMs for collaborative filtering and apply the models to a large collection of user ratings for films. Latent classes are topologically organized on a "star-like" structure. This makes orientation in rating patterns captured by latent classes easier and more systematic. The variation in film rating patterns is modelled by multinomial and binomial distributions with varying independence assumptions.

• Type: Conference
• Year: 2004
• Where: IFIP12
• Authors: Gabriela Polcicova, Peter Tiño
• Keywords: IFIP12 2004, IFIP12 2007, Latent Class Models, Latent Classes, Latent Variables