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Within a search engine, query auto-completion aims to predict the final query the user wants to enter as they type, with the aim of reducing query entry time and potentially preparing the search results in advance of query submission. There are a large number of approaches to automatically rank candidate queries for the purposes of auto-completion. However, no study exists that compares these approaches on a single dataset. Hence, in this paper, we present a comparison study between currentdoi:10.1145/2766462.2767829 dblp:conf/sigir/SantoMMO15 fatcat:h7dsbdlalzdcvmpg5cqpb6bq3a