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Syst."],"published-print":{"date-parts":[[2017,10,31]]},"abstract":"<jats:p>\n            In recent years, mobile devices have become the most popular interface for users to retrieve and access information: recent reports show that users spend significantly more time and issue more search queries on mobile devices than on desktops in the United States.\n            <jats:sup>1<\/jats:sup>\n            The accelerated growth of mobile usage brings unique opportunities to the information retrieval and data mining research communities.\n          <\/jats:p>\n          <jats:p>Mobile devices capture rich contextual and personal signals that can be leveraged to accurately predict users\u2019 intent for serving more relevant content and can even proactively provide novel zero-query recommendations. Apple Siri, Google Now, and Microsoft Cortana are recent examples of such emerging systems. Furthermore, mobile devices constantly generate a huge amount of sensor footprints (e.g., GPS, motion sensors) and user activity data (e.g., used apps) that are often missing from their desktop counterparts. These new sources of implicit and explicit user feedback are valuable for discovering actionable knowledge, and designing better systems that serve each individual the right content at the right time and location. In addition, by aggregating mobile interactions across individuals, one can infer interesting conclusions beyond search and recommendation. Generating real-time traffic estimates is one example of such applications.<\/jats:p>\n          <jats:p>This special issue focuses on research problems of search, mining, and their applications in mobile devices. Topics of interest in this special issue include but are not limited to mobile data mining and management, mobile search, personalization and recommendation, mobile user interfaces and human-computer interaction, and new applications in the mobile environment. The aim of this special issue is to bring together top experts across multiple disciplines, including information retrieval, data mining, mobile computing, and cyberphysical systems, such that academic and industrial researchers can exchange ideas and share the latest developments on the state of the art and practice of mobile search and mobile data mining.<\/jats:p>","DOI":"10.1145\/3086665","type":"journal-article","created":{"date-parts":[[2017,8,24]],"date-time":"2017-08-24T11:49:04Z","timestamp":1503575344000},"page":"1-17","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":8,"title":["Search, Mining, and Their Applications on Mobile Devices"],"prefix":"10.1145","volume":"35","author":[{"given":"Hongning","family":"Wang","sequence":"first","affiliation":[{"name":"Department of Computer Science, University of Virginia, VA, USA"}]},{"given":"Rui","family":"Li","sequence":"additional","affiliation":[{"name":"Google Inc., CA, USA"}]},{"given":"Milad","family":"Shokouhi","sequence":"additional","affiliation":[{"name":"Microsoft, Cambridge, UK"}]},{"given":"Hang","family":"Li","sequence":"additional","affiliation":[{"name":"Noah's Ark Lab of Huawei Technologies, China"}]},{"given":"Yi","family":"Chang","sequence":"additional","affiliation":[{"name":"Huawei Research America, CA, USA"}]}],"member":"320","published-online":{"date-parts":[[2017,8,24]]},"reference":[{"key":"e_1_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1145\/2600428.2609505"},{"key":"e_1_2_1_2_1","volume-title":"Proceedings of the 16th International Conference on World Wide Web (WWW\u201907)","author":"Baeza-Yates Ricardo","year":"2007","unstructured":"Ricardo Baeza-Yates , Georges Dupret , and Javier Velasco . 2007 . 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