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020 ▼a 9781088350300
035 ▼a (MiAaPQ)AAI13885794
040 ▼a MiAaPQ ▼c MiAaPQ ▼d 247004
0820 ▼a 001
1001 ▼a Guo, Wei.
24510 ▼a Understanding and Improving Mobile Reading via Scalable and Low Cost Sensing.
260 ▼a [S.l.]: ▼b University of Pittsburgh., ▼c 2019.
260 1 ▼a Ann Arbor: ▼b ProQuest Dissertations & Theses, ▼c 2019.
300 ▼a 111 p.
500 ▼a Source: Dissertations Abstracts International, Volume: 81-04, Section: B.
500 ▼a Advisor: Wang, Jingtao
5021 ▼a Thesis (Ph.D.)--University of Pittsburgh, 2019.
506 ▼a This item must not be sold to any third party vendors.
520 ▼a In recent years, due to the increasing ubiquity of Internet and mobile devices, mobile reading on smart watches and smartphones is experiencing rapid growth. Despite the great potential, new challenges are brought. Compared to traditional reading, mobile reading faces major challenges such as encountering more frequent distractions and lacking portable and efficient technique to deeply understand and improve it.Fortunately, the development of the hardware and software of mobile devices provide an opportunity to track users' behavior and physiological signals accurately in a low-cost and portable manner. In this thesis, I explored the usage of low-cost mobile sensors to solve the measurement challenges of reading.I used the low-cost mobile sensing techniques on mobile devices to understand and improve the degree and quality of reading. In this thesis, I first present SmartRSVP, a reading interface on smart watches that leverages eye-gaze contact tracking technique and heart rate sensing technique to facilitate reading under distractions. I then present Lepton, an intelligent reading system on smart phones that tracks eye-gaze periodical patterns and sensing the screen touching behavior to monitor readers' cognitions and emotions during reading. Lastly, I present StrategicReading, which uses the implicitly captured eye gaze patterns, scrolling motions, and log histories to monitor users' reading strategies and performance during multiple-sources online reading.
590 ▼a School code: 0178.
650 4 ▼a Computer science.
650 4 ▼a Artificial intelligence.
690 ▼a 0984
690 ▼a 0800
71020 ▼a University of Pittsburgh. ▼b School of Computing and Information.
7730 ▼t Dissertations Abstracts International ▼g 81-04B.
773 ▼t Dissertation Abstract International
790 ▼a 0178
791 ▼a Ph.D.
792 ▼a 2019
793 ▼a English
85640 ▼u http://www.riss.kr/pdu/ddodLink.do?id=T15491464 ▼n KERIS ▼z 이 자료의 원문은 한국교육학술정보원에서 제공합니다.
980 ▼a 202002 ▼f 2020
990 ▼a ***1816162
991 ▼a E-BOOK