In information retrieval, query auto completion (QAC), also known as typeahead [**ao et al.,
2013, Cai et al., 2014b] and auto-complete suggestion [Jain and Mishne, 2010], refers to the …

Chinese Grammatical Error Correction (CGEC) is both a challenging NLP task and a
common application in human daily life. Recently, many data-driven approaches are …

Query auto-completion (QAC) systems typically suggest queries that have previously been
observed in search logs. Given a partial user query, the system looks up this query prefix …

Chinese Text Error Correction (CTEC) aims to detect and correct errors in the input text,
which benefits human's daily life and various downstream tasks. Recent approaches mainly …

Query auto-completion (QAC) is a common interactive feature that assists users in
formulating queries by providing completion suggestions as they type. In order for QAC to …

Query Auto Completion (QAC) suggests possible queries to web search users from the
moment they start entering a query. This popular feature of web search engines is thought to …

In high-dimensional feature spaces traditional clustering algorithms tend to break down in
terms of efficiency and quality. Nevertheless, the data sets often contain clusters which are …

Huge amounts of search log data have been accumulated at Web search engines.
Currently, a popular Web search engine may receive billions of queries and collect terabytes …

Query auto-completion (QAC) facilitates faster user query input by predicting users' intended
queries. Most QAC algorithms take a learning-based approach to incorporate various …

Virtually every modern search application, either desktop, web, or mobile, features some
kind of query auto-completion. In its basic form, the problem consists in retrieving from a …