Key data for cloud computing based on ensemble clustering approximate analysis Online publication date: Sat, 09-Jun-2018
by Zou Yu; Qin Zhong Ping
International Journal of Reasoning-based Intelligent Systems (IJRIS), Vol. 10, No. 2, 2018
Abstract: To realise multi-label classification of text and meanwhile reduce calculation complexity and keep classification precision, dimensionality-reduction clustering method for fuzzy association of text multi-label based on cluster classification has been proposed. In text classification, it usually involves enormous feature numbers, which may cause curse of dimensionality. In addition, classification region can not always keep convex characteristics. It can be non-convex region composed of several overlapping or intersecting sub-regions. Above mentioned automatic classification system may require enormous memory requirement or has poor classification performance. Hence, new multi-label text classification method is proposed to overcome these problems in combination with fuzzy association technology. Fuzzy association evaluation is adopted to transform high-dimension text to low-dimension fuzzy association vector, thus avoiding curse of dimensionality. Experiment results show that the proposed method can more effectively classify text multi-label problem.
Online publication date: Sat, 09-Jun-2018
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Reasoning-based Intelligent Systems (IJRIS):
Login with your Inderscience username and password:
Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.
If you still need assistance, please email firstname.lastname@example.org