DocumentCode :
891340
Title :
Efficient Monitoring Algorithm for Fast News Alerts
Author :
Sia, Ka Cheung ; Cho, Junghoo ; Cho, Hyun-Kyu
Author_Institution :
Univ. of California, Los Angeles
Volume :
19
Issue :
7
fYear :
2007
fDate :
7/1/2007 12:00:00 AM
Firstpage :
950
Lastpage :
961
Abstract :
Recently, there has been a dramatic increase in the use of XML data to deliver information over the Web. Personal Weblogs, news Web sites, and discussion forums are now publishing RSS feeds for their subscribers to retrieve new postings. As the popularity of personal Weblogs and RSS feeds grows rapidly, RSS aggregation services and blog search engines have appeared, which try to provide a central access point for simpler access and discovery of new content from a large number of diverse RSS sources. In this paper, we study how the RSS aggregation services should monitor the data sources to retrieve new content quickly using minimal resources and to provide its subscribers with fast news alerts. We believe that the change characteristics of RSS sources and the general user access behavior pose distinct requirements that make this task significantly different from the traditional index refresh problem for Web search engines. Our studies on a collection of 10,000 RSS feeds reveal some general characteristics of the RSS feeds and show that, with proper resource allocation and scheduling, the RSS aggregator provides news alerts significantly faster than the best existing approach.
Keywords :
XML; information resources; information retrieval; monitoring; resource allocation; scheduling; search engines; RSS aggregation service; Web search engine; XML data; fast news alerts; information retrieval; monitoring algorithm; resource allocation; scheduling; user access behavior; Discussion forums; Feeds; Information retrieval; Information services; Internet; Monitoring; Publishing; Search engines; Web sites; XML; Information search and retrieval; alert services.; online information services; performance evaluation; user profiles;
fLanguage :
English
Journal_Title :
Knowledge and Data Engineering, IEEE Transactions on
Publisher :
ieee
ISSN :
1041-4347
Type :
jour
DOI :
10.1109/TKDE.2007.1041
Filename :
4216310
Link To Document :
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