Semi-supervised Category-specific Review Tagging on Indonesian E-Commerce Product Reviews
Meng Sun, Marie Stephen Leo, Eram Munawwar, Paul C. Condylis, Sheng-yi Kong, Seong Per Lee, Albert Hidayat, Muhamad Danang Kerianto · 2020
Product reviews are a huge source of natural language data in e-commerce applications.Several millions of customers write reviews regarding a variety of topics.We categorize these topics into two groups as either "category-specific" topics or as "generic" topics that span multiple product categories.While we can use a supervised learning approach to tag review text for generic topics, it is impossible to use supervised approaches to tag category-specific topics due to the sheer number of possible topics for each category.In this paper, we present an approach to tag each review with several product category-specific tags on Indonesian language product reviews using a semi-supervised approach.We show that our proposed method can work at scale on real product reviews at Tokopedia 1 , a major e-commerce platform in Indonesia.Manual evaluation shows that the proposed method can efficiently generate category-specific product tags.