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Lightweight methods for large‐scale product categorization

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  • Eli Cortez
  • Mauro Rojas Herrera
  • Altigran S. da Silva
  • Edleno S. de Moura
  • Marden Neubert

Abstract

In this article, we present a study about classification methods for large‐scale categorization of product offers on e‐shopping web sites. We present a study about the performance of previously proposed approaches and deployed a probabilistic approach to model the classification problem. We also studied an alternative way of modeling information about the description of product offers and investigated the usage of price and store of product offers as features adopted in the classification process. Our experiments used two collections of over a million product offers previously categorized by human editors and taxonomies of hundreds of categories from a real e‐shopping web site. In these experiments, our method achieved an improvement of up to 9% in the quality of the categorization in comparison with the best baseline we have found.

Suggested Citation

  • Eli Cortez & Mauro Rojas Herrera & Altigran S. da Silva & Edleno S. de Moura & Marden Neubert, 2011. "Lightweight methods for large‐scale product categorization," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 62(9), pages 1839-1848, September.
    • Handle: RePEc:bla:jamist:v:62:y:2011:i:9:p:1839-1848
    DOI: 10.1002/asi.21586
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