TY - JOUR
T1 - IoT-based personalized NIE content recommendation system
AU - Kim, Yongsung
AU - Jung, Seungwon
AU - Ji, Seonmi
AU - Hwang, Eenjun
AU - Rho, Seungmin
N1 - Funding Information:
Acknowledgments This work was partly supported by Institute for Information & communications Technology Promotion (IITP) grant funded by the Korea government (MSIT) (No. R0190-16-2012, High Performance Big Data Analytics Platform Performance Acceleration Technologies Development) and Basic Science Research Program through the National Research Foundation of Korea(NRF) funded by the Ministry of Education(NRF-2016R1D1A1A09919590).
Publisher Copyright:
© 2018, Springer Science+Business Media, LLC, part of Springer Nature.
PY - 2019/2/1
Y1 - 2019/2/1
N2 - Recently, the Internet of Things (IoT) has become a popular topic and a dominant trend in various fields, such as healthcare, agriculture, manufacturing, and transportation. In particular, in the field of education, it has become a popular tool to improve learners’ interests and achievements by making them interact with various devices in and out of the classroom. Lessons in newspaper in education (NIE), which uses newspapers as an educational resource, have started to utilize it. For instance, by analyzing the data generated from a learner’s device, such as Raspberry Pi, appropriate news and related multimedia data can be provided to the learners as learning materials to support the lesson. However, as news and multimedia data are scattered in a wide variety of forms, it is very difficult to select appropriate ones for the learner. In this paper, we propose a news and related multimedia recommendation scheme based on IoT for supporting NIE lessons. Specifically, news and related multimedia data are collected from the Web, and they are integrated and stored into the server. After that, the learner can easily browse such contents using a mobile device through personalized visualization, which increase the efficiency of NIE lessons. To show the effectiveness of our scheme, we implemented a prototype system and performed various experiments. We present some of the results.
AB - Recently, the Internet of Things (IoT) has become a popular topic and a dominant trend in various fields, such as healthcare, agriculture, manufacturing, and transportation. In particular, in the field of education, it has become a popular tool to improve learners’ interests and achievements by making them interact with various devices in and out of the classroom. Lessons in newspaper in education (NIE), which uses newspapers as an educational resource, have started to utilize it. For instance, by analyzing the data generated from a learner’s device, such as Raspberry Pi, appropriate news and related multimedia data can be provided to the learners as learning materials to support the lesson. However, as news and multimedia data are scattered in a wide variety of forms, it is very difficult to select appropriate ones for the learner. In this paper, we propose a news and related multimedia recommendation scheme based on IoT for supporting NIE lessons. Specifically, news and related multimedia data are collected from the Web, and they are integrated and stored into the server. After that, the learner can easily browse such contents using a mobile device through personalized visualization, which increase the efficiency of NIE lessons. To show the effectiveness of our scheme, we implemented a prototype system and performed various experiments. We present some of the results.
KW - Data integration
KW - Deep learning
KW - Internet of things
KW - Multimedia in education
KW - News in education
KW - Semantic web
UR - http://www.scopus.com/inward/record.url?scp=85040667061&partnerID=8YFLogxK
U2 - 10.1007/s11042-018-5610-8
DO - 10.1007/s11042-018-5610-8
M3 - Article
AN - SCOPUS:85040667061
SN - 1380-7501
VL - 78
SP - 3009
EP - 3043
JO - Multimedia Tools and Applications
JF - Multimedia Tools and Applications
IS - 3
ER -