  Entity-based semantic search has been widely adopted in modern search engines
to improve search accuracy by understanding users' intent. In e-commerce, an
accurate and complete product type (PT) ontology is essential for recognizing
product entities in queries and retrieving relevant products from catalog.
However, finding product types (PTs) to construct such an ontology is usually
expensive due to the considerable amount of human efforts it may involve. In
this work, we propose an active learning framework that efficiently utilizes
domain experts' knowledge for PT discovery. We also show the quality and
coverage of the resulting PTs in the experiment results.
