Title :
Web Service to Deliver Filtered RSS Items to a Mobile Application
Author :
Sajjanhar, Atul ; Zhao, Ying
Author_Institution :
Sch. of Inf. Technol., Deakin Univ., Burwood, VIC, Australia
Abstract :
In the past decade there has been massive growth of data on the internet. Many people rely on XML based RSS feeds to receive updates from websites. In this paper, we propose a method for managing the RSS feeds from various news websites. A web service is developed to deliver filtered news items from RSS feeds to a mobile client. Each news item is indexed, subsequently, the indexes are used for filtering news items. Indexing is done in two steps. First, classical text categorization algorithms are used to assign a category to each news item, second, geoparsing is used to assign geolocation data to each news item. An android application is developed to access filtered news items by consuming the proposed web service. A prototype is implemented using Rapid miner 5.0 as the data mining tool and SVM as the classification algorithm. Geoparsing and geocoding web services, and Android API are used to implement location-based access to news items. Experimental results prove that the proposed approach is effective and saves a significant amount of information overload processing time.
Keywords :
Web services; Web sites; XML; application program interfaces; data mining; indexing; information filtering; mobile computing; pattern classification; support vector machines; text analysis; Android API; Internet; RSS item filtering; Rapid miner 5.0; SVM; Web service geocoding; XML based RSS feeds; category assignment; classical text categorization algorithms; classification algorithm; data mining tool; geolocation data assignment; geoparsing; indexing; mobile application; news Websites; news item filtering; Androids; Feeds; Geology; Humanoid robots; Support vector machines; Text categorization; Web services; Geoparsing; SVM; Web service; text classification;
Conference_Titel :
ChinaGrid Annual Conference (ChinaGrid), 2012 Seventh
Conference_Location :
Beijing
Print_ISBN :
978-1-4673-2623-0
Electronic_ISBN :
978-0-7695-4816-6
DOI :
10.1109/ChinaGrid.2012.8