  Query Auto-Completion(QAC), as an important part of the modern search engine,
plays a key role in complementing user queries and helping them refine their
search intentions.Today's QAC systems in real-world scenarios face two major
challenges:1)intention equivocality(IE): during the user's typing process,the
prefix often contains a combination of characters and subwords, which makes the
current intention ambiguous and difficult to model.2)intention transfer
(IT):previous works make personalized recommendations based on users'
historical sequences, but ignore the search intention transfer.However, the
current intention extracted from prefix may be contrary to the historical
preferences.
