By Topic

Autonomic collaborative RSS: An implementation of autonomic data using data killing patterns

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

5 Author(s)
Wallace A. Pinheiro ; COPPE/UFRJ, Federal University of Rio de Janeiro, Brazil ; Marcelino C. O. Silva ; Ricardo Barros ; Geraldo Xexeo
more authors

Corporate and personal computers are flooded by a huge amount of data. Among them, there are irrelevant, similar, false, wrong and obsolete data. Besides, the treatment of this data is relatively complex. Systems need to check, transform, adapt, and summarize data in order to use it. These activities spend time and money of many companies that should be concerned for business rules. In RSS feeds, we have these problems: the users receive a big number of news, sometimes irrelevant or duplicated. The tools to cope with these data do not provide efficient mechanisms to manager information overload. To reach this goal, it is necessary to introduce a new complexity to feed readers, what is sometimes undesirable. Therefore, we propose the autonomic collaborative RSS that transfers the system complexity to data, facilitating the system development. At the same time, it allows to incorporate data treatment rules, as well, data filtering through data killing patterns.

Published in:

Computer Supported Cooperative Work in Design, 2009. CSCWD 2009. 13th International Conference on

Date of Conference:

22-24 April 2009