@inproceedings{4f79ed4f812e4b98ab3b87b746763d10,
title = "Towards mobile query auto-completion: An efficient mobile application-Aware approach",
abstract = "We study the new mobile query auto-completion (QAC) problem to exploit mobile devices' exclusive signals, such as those related to mobile applications (apps). We propose AppAware, a novel QAC model using installed app and recently opened app signals to suggest queries for matching input prefixes on mobile devices. To overcome the challenge of noisy and voluminous signals, AppAware optimizes composite objectives with a lighter processing cost at a linear rate of convergence. We conduct experiments on a large commercial data set of mobile queries and apps. Installed app and recently opened app signals consistently and significantly boost the accuracy of various baseline QAC models on mobile devices.",
keywords = "Mobile Application, Mobile Device, Query Auto-Completion",
author = "Aston Zhang and Amit Goyal and Ricardo Baeza-Yates and Yi Chang and Jiawei Han and Gunter, {Carl A.} and Hongbo Deng",
year = "2016",
doi = "10.1145/2872427.2882977",
language = "English (US)",
series = "25th International World Wide Web Conference, WWW 2016",
publisher = "International World Wide Web Conferences Steering Committee",
pages = "579--590",
booktitle = "25th International World Wide Web Conference, WWW 2016",
note = "25th International World Wide Web Conference, WWW 2016 ; Conference date: 11-04-2016 Through 15-04-2016",
}