Deep Learning Methods for Query Auto Completion

Query Auto Completion (QAC) aims to help users reach their search intent faster and is a gateway to search for users. Everyday, Billions of keystrokes across 100s of languages are served by Bing Autosuggest in less than 100 ms. The expected suggestions could differ depending on user demography, previous search queries and current trends. In general, the suggestions in the AutoSuggest block are expected to be relevant, personalized, fresh, diverse and need to be guarded against being defective, hateful, adult or offensive in any way. In this tutorial, we will talk how state-of-the-art deep learning models have been leveraged for ranking in QAC, personalization, spell corrections and natural language generation (NLG) for QAC.