Meng Sun author Marie Stephen Leo author Eram Munawwar author Paul C Condylis author Sheng-yi Kong author Seong Per Lee author Albert Hidayat author Muhamad Danang Kerianto author 2020-jul text Association for Computational Linguistics Seattle, WA, USA conference publication 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, a major e-commerce platform in Indonesia. Manual evaluation shows that the proposed method can efficiently generate category-specific product tags. sun-etal-2020-semi https://www.aclweb.org/anthology/2020.ecnlp-1.9 2020-jul 59 63