| License: Creative Commons Attribution 4.0 PDF - Published Version (725kB) |
- URN to cite this document:
- urn:nbn:de:bvb:355-epub-509527
- DOI to cite this document:
- 10.5283/epub.50952
This publication is part of the DEAL contract with Springer.
Abstract
The increasing importance of online distribution channels is paralleled by a rising interest in gaining insights into the customer journey and browsing behavior. We evaluate several machine learning methods (latent Dirichlet allocation, correlated topic model, structural topic model, replicated softmax model) with respect to their ability to reproduce the browsing behavior of households across ...
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