Title :
Delivering Categorized News Items Using RSS Feeds and Web Services
Author :
Saha, Subrata ; Sajjanhar, Atul ; Gao, Shang ; Dew, Robert ; Zhao, Ying
Author_Institution :
Sch. of Inf. Technol., Deakin Univ., Burwood, VIC, Australia
fDate :
June 29 2010-July 1 2010
Abstract :
In the past decade the massive growth of the Internet brought huge changes in the way humans live their daily life; however, the biggest concern with rapid growth of digital information is how to efficiently manage and filter unwanted data. In this paper, we propose a method for managing RSS feeds from various news websites. A Web service was developed to provide filtered news items extracted from RSS feeds and these were categorized based on classical text categorization algorithms. A client application consuming this Web service retrieves and displays such filtered information. A prototype was implemented using Rapidminer 4.3 as a data mining tool and SVM as a classification algorithm. Experimental results suggest that the proposed method is effective and saves a significant amount of user processing time.
Keywords :
Web services; Web sites; data mining; information filtering; support vector machines; text analysis; Internet; RSS feeds; Rapidminer 4.3; SVM; Web services; categorized news item; classification algorithm; data mining; news Web sites; text categorization algorithm; Business; Classification algorithms; Feeds; Support vector machines; Text categorization; Training; Web services; Really Simple Syndication (RSS); Support Vector Machines (SVM); text categorization; text classification; web services;
Conference_Titel :
Computer and Information Technology (CIT), 2010 IEEE 10th International Conference on
Conference_Location :
Bradford
Print_ISBN :
978-1-4244-7547-6
DOI :
10.1109/CIT.2010.136