Research history generation from metainformation of research papers using maximum margin clustering
by Manh Cuong Nguyen; Daichi Kato; Taiichi Hashimoto; Haruo Yokota
International Journal of Business Intelligence and Data Mining (IJBIDM), Vol. 7, No. 3, 2012

Abstract: Recently, analysing research papers to understand research trends researcher's research topics automatically from metainformation of research papers published on the internet. Our method is based on Maximum Margin Clustering (MMC). We describe how to represent research papers in form of vectors using metainformation about them and how to initialise the hyperplane for MMC automatically. In the experiments, we show that the purity of our method is higher than that achieved in previous work based on k-Means (0.58 vs 0.35) and entropy of our method is lower than that of previous work (0.415 vs 0.47). Experiment results also illustrates that keyword information of research papers affects the most to clustering result.

Online publication date: Wed, 12-Nov-2014

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
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 Business Intelligence and Data Mining (IJBIDM):
Login with your Inderscience username and password:

Username:        Password:          Forgotten your 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 subs@inderscience.com