TY - GEN
T1 - Detection and recommendation of experts/authorities of Mendeley and Twitter topics for learning stimulation
AU - León-Ullauri, Benito B.
AU - Bravo-Torres, Jack F.
AU - Contreras-Chacón, Roque D.
AU - Yépez-Alulema, Jennifer A.
AU - Cuji-Dután, Diego A.
AU - Vintimilla-Tapia, Paúl E.
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2017/12/19
Y1 - 2017/12/19
N2 - Nowadays, life unfolds in a digitised world, in which, each person can have access to a huge amount of information through the use of Internet. In this situation, most of daily activities are being influenced by a new kind of society that allows ubiquitous and instantaneous interaction among its members. The creation of social platforms (SPs) has strengthened human relationships at such point that any person can globalise their knowledge, experience, and opinion about a specific topic. According to the society, this can be seen as an interpersonal relationships evolution; however, this sets up an over-information problem. Looking at the educational field, such problem is a sensitive subject due to students need only experts/authorities knowledge. In order to provide a solution to this situation, in this paper, we propose the development of an experts/authorities recommender system, based on Mendeley and Twitter, to improve educational processes.
AB - Nowadays, life unfolds in a digitised world, in which, each person can have access to a huge amount of information through the use of Internet. In this situation, most of daily activities are being influenced by a new kind of society that allows ubiquitous and instantaneous interaction among its members. The creation of social platforms (SPs) has strengthened human relationships at such point that any person can globalise their knowledge, experience, and opinion about a specific topic. According to the society, this can be seen as an interpersonal relationships evolution; however, this sets up an over-information problem. Looking at the educational field, such problem is a sensitive subject due to students need only experts/authorities knowledge. In order to provide a solution to this situation, in this paper, we propose the development of an experts/authorities recommender system, based on Mendeley and Twitter, to improve educational processes.
KW - Authorities detection
KW - Experts detection
KW - Mendeley
KW - Recommender system
KW - Twitter
UR - https://www.scopus.com/pages/publications/85042733457
U2 - 10.1109/CHILECON.2017.8229643
DO - 10.1109/CHILECON.2017.8229643
M3 - Conference contribution
AN - SCOPUS:85042733457
T3 - 2017 CHILEAN Conference on Electrical, Electronics Engineering, Information and Communication Technologies, CHILECON 2017 - Proceedings
SP - 1
EP - 5
BT - 2017 CHILEAN Conference on Electrical, Electronics Engineering, Information and Communication Technologies, CHILECON 2017 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2017 CHILEAN Conference on Electrical, Electronics Engineering, Information and Communication Technologies, CHILECON 2017
Y2 - 18 October 2017 through 20 October 2017
ER -