The full text of this article

 

Stream-based live entity resolution approach with adaptive duplicate count strategy
by Kun Ma; Bo Yang
International Journal of Web and Grid Services (IJWGS), Vol. 13, No. 3, 2017

 

Abstract: Recently, researchers have been more concerned about large-scale news and tweet data generated by the social media. Some cloud service providers utilise the data to find public sentiments for the tenants. The challenge is how to clean the big data in the cloud before making further analysis. To address this issue, we propose a new live entity resolution approach at a time to find duplicates from the news and tweet data. We investigate possible solutions to address live entity resolution in the cloud, to make sliding window size adaptive using multistep distance and window size dependent duplicate count strategy with alterable window step, and find duplicates by overlapping boundary objects in adjacent blocks. Finally, our experimental evaluation based on the news data on large datasets shows the high effectiveness and efficiency of the proposed approaches.

Online publication date: Mon, 03-Jul-2017

 

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 Web and Grid Services (IJWGS):
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