Title
Research On Result Integration Mechanism Based On Crowd Wisdom To Achieve The Correlation Of Resources And Knowledge Points
Abstract
Correlating massive resources with knowledge points can help to achieve effective aggregation of resources and to improve learners learning efficiency and learning experience. This paper proposes a result integration mechanism based on the crowd wisdom to determine the association of learning resources and knowledge points, and ensure the final annotation result has certain credibility. Accordingly, we propose a user confidence to evaluate the user's ability to complete the tasks. The experimental results show that the proposed algorithms improve the accuracy and efficiency comparing with the majority voting method, and algorithm to estimate user's confidence can converge to actual value efficiently.
Year
DOI
Venue
2018
10.1007/978-3-319-99737-7_60
INNOVATIVE TECHNOLOGIES AND LEARNING, ICITL 2018
Keywords
DocType
Volume
The result integration mechanism, The crowd wisdom, Task result confidence, User confidence
Conference
11003
ISSN
Citations 
PageRank 
0302-9743
1
0.35
References 
Authors
0
5
Name
Order
Citations
PageRank
Xu Du13715.92
Fan Zhang222969.82
Mingyan Zhang321.38
Shuai Xu42710.78
Mengjin Liu510.35