TY - GEN
T1 - Hybrid Fuzzy Recommendation System for Enhanced E-learning
AU - Padmaja Appalla, Appalla
AU - Rajalakshmi Selvaraj, Selvaraj
AU - Kuthadi, Venu Madhav
AU - Marwala, Tshilidzi
N1 - Publisher Copyright:
© 2018, Springer Nature Singapore Pte Ltd.
PY - 2018
Y1 - 2018
N2 - The heterogeneous e-learning materials are generated in the progress of online e-learning technique. The system of e-learning is providing huge opportunities for learning online for learners with enhanced and efficient practices of learning. The system of e-learning needs to cater for the individual learner requirements including learner’s profile and activities of learning in the form of tree structure. There are several issues of pedagogical learning. In case of learning phenomenon, this is too difficult for any learner or user to select their suitable learning resources without having exact background knowledge. To address these issues, this research is proposing two enhanced techniques called as Hybrid Fuzzy-based Matching Recommendation Algorithm and Collaborative Sequential Map Filtering Algorithm. This proposed approach recommends a new method to assist users on their individual as well as collaborative learning methods for accessing learning resources.
AB - The heterogeneous e-learning materials are generated in the progress of online e-learning technique. The system of e-learning is providing huge opportunities for learning online for learners with enhanced and efficient practices of learning. The system of e-learning needs to cater for the individual learner requirements including learner’s profile and activities of learning in the form of tree structure. There are several issues of pedagogical learning. In case of learning phenomenon, this is too difficult for any learner or user to select their suitable learning resources without having exact background knowledge. To address these issues, this research is proposing two enhanced techniques called as Hybrid Fuzzy-based Matching Recommendation Algorithm and Collaborative Sequential Map Filtering Algorithm. This proposed approach recommends a new method to assist users on their individual as well as collaborative learning methods for accessing learning resources.
KW - Collaborative filter
KW - Fuzzy tree matching
KW - Knowledge-based recommendation
KW - Personalize
KW - Sequential map
UR - http://www.scopus.com/inward/record.url?scp=85040012165&partnerID=8YFLogxK
U2 - 10.1007/978-981-10-4762-6_3
DO - 10.1007/978-981-10-4762-6_3
M3 - Conference contribution
AN - SCOPUS:85040012165
SN - 9789811047619
T3 - Lecture Notes in Electrical Engineering
SP - 21
EP - 32
BT - Advances in Systems, Control and Automation - ETAEERE-2016
A2 - Konkani, Avinash
A2 - Bera, Rabindranath
A2 - Paul, Samrat
PB - Springer Verlag
T2 - 1st International Conference on Emerging Trends and Advances in Electrical Engineering and Renewable Energy, ETAEERE 2016
Y2 - 17 December 2016 through 18 December 2016
ER -