TY - GEN
T1 - Mobile Book Reader Based on Reading Behavior Characteristics
AU - Xu, Ruichao
AU - Gao, Zhigang
AU - Wu, Bo
AU - Diao, Wenjie
AU - Huang, Yucai
AU - Zhao, Wei
N1 - Funding Information:
ACKNOWLEDGMENT This work is supported by the National Natural Science Foundation of China under Grants No. 61877015, No. 61572164, No. 61473109, No. 61272315, the ReformProject of Higher Education in Zhejiang under Grants No. jg20160071, Zhejiang ProvincialNatural Science Foundation under Grant No. LY19F020016, and the project of education planning in Zhejiang under Grants No. 2018SCG005.
Publisher Copyright:
© 2020 IEEE.
PY - 2020/8
Y1 - 2020/8
N2 - With the rapid development of the network communication technology and the popularity of mobile devices, mobile reading has become an essential reading approach. Aiming at the shortcomings of reading applications on the mobile platform such as the deficiency on the strategy of caching books and the lack of predicting reading pages with current power, we developed a mobile book reader (MBR) for android devices. It can dynamically cache the page contents to be read according to users' reading speed, and predict the number of reading pages supported by remaining power in text and voice reading modes. We tested the space occupancy of cache files and remaining reading time. The experimental results show that the cache strategy in MBR can effectively relieve the storage pressure of the device, and the prediction of remaining reading time helps users to arrange the reading plan.
AB - With the rapid development of the network communication technology and the popularity of mobile devices, mobile reading has become an essential reading approach. Aiming at the shortcomings of reading applications on the mobile platform such as the deficiency on the strategy of caching books and the lack of predicting reading pages with current power, we developed a mobile book reader (MBR) for android devices. It can dynamically cache the page contents to be read according to users' reading speed, and predict the number of reading pages supported by remaining power in text and voice reading modes. We tested the space occupancy of cache files and remaining reading time. The experimental results show that the cache strategy in MBR can effectively relieve the storage pressure of the device, and the prediction of remaining reading time helps users to arrange the reading plan.
KW - Cache
KW - Mobile Reading
KW - Pages Prediction
KW - Reading Speed
UR - http://www.scopus.com/inward/record.url?scp=85097656914&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85097656914&partnerID=8YFLogxK
U2 - 10.1109/DASC-PICom-CBDCom-CyberSciTech49142.2020.00060
DO - 10.1109/DASC-PICom-CBDCom-CyberSciTech49142.2020.00060
M3 - Conference contribution
AN - SCOPUS:85097656914
T3 - Proceedings - IEEE 18th International Conference on Dependable, Autonomic and Secure Computing, IEEE 18th International Conference on Pervasive Intelligence and Computing, IEEE 6th International Conference on Cloud and Big Data Computing and IEEE 5th Cyber Science and Technology Congress, DASC/PiCom/CBDCom/CyberSciTech 2020
SP - 306
EP - 311
BT - Proceedings - IEEE 18th International Conference on Dependable, Autonomic and Secure Computing, IEEE 18th International Conference on Pervasive Intelligence and Computing, IEEE 6th International Conference on Cloud and Big Data Computing and IEEE 5th Cyber Science and Technology Congress, DASC/PiCom/CBDCom/CyberSciTech 2020
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 18th IEEE International Conference on Dependable, Autonomic and Secure Computing, 18th IEEE International Conference on Pervasive Intelligence and Computing, 6th IEEE International Conference on Cloud and Big Data Computing and 5th IEEE Cyber Science and Technology Congress, DASC/PiCom/CBDCom/CyberSciTech 2020
Y2 - 17 August 2020 through 24 August 2020
ER -