자료유형 | 학위논문 |
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서명/저자사항 | Understanding and Improving Mobile Reading via Scalable and Low Cost Sensing. |
개인저자 | Guo, Wei. |
단체저자명 | University of Pittsburgh. School of Computing and Information. |
발행사항 | [S.l.]: University of Pittsburgh., 2019. |
발행사항 | Ann Arbor: ProQuest Dissertations & Theses, 2019. |
형태사항 | 111 p. |
기본자료 저록 | Dissertations Abstracts International 81-04B. Dissertation Abstract International |
ISBN | 9781088350300 |
학위논문주기 | Thesis (Ph.D.)--University of Pittsburgh, 2019. |
일반주기 |
Source: Dissertations Abstracts International, Volume: 81-04, Section: B.
Advisor: Wang, Jingtao |
이용제한사항 | This item must not be sold to any third party vendors. |
요약 | 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. |
일반주제명 | Computer science. Artificial intelligence. |
언어 | 영어 |
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