A Hybrid Web Recommendation System based on the Improved Association Rule Mining Algorithm

Wanaskar, Ujwala; Vij, Sheetal; Mukhopadhyay, Debajyoti

doi:10.48550/arxiv.1311.7204

Cited by 1 publication

(1 citation statement)

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“…The various recommendation approaches are context-aware approaches (Wang, Meng, & Zhang, 2012), semantic-based approaches (Di Noia, Mirizzi, Ostuni, Romito, & Zanker, 2012), cross domain-based approaches (Tang, Wu, Sun, & Su, 2012), peer-to-peer approaches (Kim, Kim,& Cho, 2008) and cross-lingual approaches (Schmidt, Scholl, Rensing, & Steinmetz, 2011). A new mining approach presented by Ujwala Wanaskar (2013) based on the combination of weighted association rule mining and text mining shows the best performance improvement compared to the existing methods.…”

Section: Related Researchmentioning

confidence: 99%

Design of Open Content Social Learning based on the Activities of Learner and Similar Learners

John

Jayakumar

Thavavel

et al. 2017

International Journal of Distance Education Technologies

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Teaching and learning are increasingly taking advantage of the rapid growth in Internet resources, open content, mobile technologies and social media platforms. However, due to the generally unstructured nature and overwhelming quantity of learning content, effective learning remains challenging. In an effort to close this gap, the authors designed and built an Open Content Social Learning (OCSL) system that compares different pedagogical strategies and algorithms intended to improve learning. Their results have shown increased effectiveness when recommending learning activities in a pedagogically appropriate order based on learning goals, historical learning preferences, and behaviors from other learners who had similar goals.

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