Title
Design of a Location-based Word Recommendation System Based on Association Rule Mining Analysis
Abstract
Association rule mining is the process of discovering new knowledge and non-trivial patterns hidden in textual datasets. This approach is often used by learning analytics researchers and practitioners for exploring unique types of data collected from various educational environments. By leveraging association rule mining, this study aims at providing a solution to a critical challenge that most of the location-based informal learning tools face namely, the limited scopes to learn new words. Hence, the purpose of this work is to design a word recommendation system that can analyze a learner's previously learned words in order to suggest new vocabulary that can be acquired in a particular learning location. We designed a study and explored a dataset for uncovering the insight of language learners' learning behaviors. 20 EFL (English as Foreign Language) learners' data, whose learning location was Tokushima region of Japan, is analyzed by using association rule mining technique. The result indicates that-First, in informal learning context, EFL learners' word learning interests vary much from each other although the learning location is same; and Second, a word recommendation system can be introduced by using association rule mining analysis; however, the possibility of getting highly associated words are low compared with random words.
Year
DOI
Venue
2019
10.1109/IIAI-AAI.2019.00057
2019 8th International Congress on Advanced Applied Informatics (IIAI-AAI)
Keywords
Field
DocType
Association rule mining,Location-based word recommendation,optimize learning path,ubiquitous learning,word cooccurrence
Recommender system,Informal learning,Learning analytics,Computer science,Data type,Association rule learning,Artificial intelligence,Natural language processing,Word learning,Vocabulary,Foreign language
Conference
ISBN
Citations 
PageRank 
978-1-7281-2628-9
0
0.34
References 
Authors
1
7
Name
Order
Citations
PageRank
Mohammad Nehal Hasnine100.34
Gökhan Akçapinar210.75
Brendan Flanagan32915.32
Kousuke Mouri45514.67
Hiroaki Ogata579696.69
Keiichi Kaneko618939.19
Noriko Uosaki77317.34