KDD2023
CADENCE: Offline Category Constrained and Diverse Query Generation for E-commerce Autosuggest
Abhinav Anand, Surender Kumar, Nandeesh Kumar, Samir Shah
Abstract
Query AutoComplete (QAC) or AutoSuggest is the first place of user interaction with an e-commerce search engine. It is critical for the QAC system to suggest relevant and well-formed queries for multiple possible user intents. Suggesting only the historical user queries fails in the case of infrequent or new prefixes. Much of the recent works generate synthetic candidates using models trained on user queries and thus have these issues: a) cold start problem as new products in the catalogue fail to get visibility due to lack of representation in user queries b) poor quality of generated candidates due to concept drift and c) low diversity/coverage of attributes such as brand, color & other facets in generated candidates.