Structuring e-commerce inventory

  • Authors:
  • Karin Mauge;Khash Rohanimanesh;Jean-David Ruvini

  • Affiliations:
  • eBay Research Labs, San Jose, CA;eBay Research Labs, San Jose, CA;eBay Research Labs, San Jose, CA

  • Venue:
  • ACL '12 Proceedings of the 50th Annual Meeting of the Association for Computational Linguistics: Long Papers - Volume 1
  • Year:
  • 2012

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Abstract

Large e-commerce enterprises feature millions of items entered daily by a large variety of sellers. While some sellers provide rich, structured descriptions of their items, a vast majority of them provide unstructured natural language descriptions. In the paper we present a 2 steps method for structuring items into descriptive properties. The first step consists in unsupervised property discovery and extraction. The second step involves supervised property synonym discovery using a maximum entropy based clustering algorithm. We evaluate our method on a year worth of e-commerce data and show that it achieves excellent precision with good recall.