Towards Analyzing the Impact of Diversity and Cardinality on the Quality of Collective Prediction Using Interval Estimates

Tóm tắt:

Recently, many research results have indicated that diversity is the most important characteristic of crowd-based applications. However, it is a point estimates-based finding in which single values are used as the representation of individual predictions on a real-life cognition task. This paper presents a study on how cardinality and diversity influence the quality of collective prediction using interval estimates. By means of computational experiments, we have found that these factors positively influence the quality of collective prediction. Besides, the results also indicate that the hypothesis "the higher the diversity, the better the quality of collective prediction" is true. Furthermore, the findings also reveal a threshold of cardinality in which its increase does not significantly influence the quality of collective prediction.

Tác giả: Van Du Nguyen, Hai Bang Truong, Ngoc Thanh Nguyen

Từ khóa: Wisdom of crowds, collective intelligence, interval estimates

Tạp chí: International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems 2019/IEA/AIE 2019: Advances and Trends in Artificial Intelligence. From Theory to Practice pp 79-86

Chỉ số: Print ISBN: 978-3-030-22998-6; Online ISBN: 978-3-030-22999-3

Link tải: https://link.springer.com/chapter/10.1007/978-3-030-22999-3_8