Everyone likes shopping! Multi-class product categorization for e-Commerce

Abstract

Online shopping caters the needs of millions of users on a daily basis. To build an accurate system that can retrieve relevant products for a query like "MB252 with travel bags" one requires product and query categorization mechanisms, which classify the text as Home&Garden>Kitchen&Dining>Kitchen Appliances>Blenders. One of the biggest challenges in e-Commerce is that providers like Amazon, e-Bay, Google, Yahoo! and Walmart organize products into different product taxonomies making it hard and time-consuming for sellers to categorize goods for each shopping platform. To address this challenge, we propose an automatic product categorization mechanism, which for a given product title assigns the correct product category from a taxonomy. We conducted an empirical evaluation on 445, 408 product titles and used a rich product taxonomy of 319 categories organized into 6 levels. We compared performance against multiple algorithms and found that the best performing system reaches .88 f-score.