Aggregated cross-media news visualization and personalization

Rohr, Cyril & Tjondronegoro, Dian W. (2008) Aggregated cross-media news visualization and personalization. In Lew, Michael S., Del Bimbo, Alberto, & Bakker, Erwin M. (Eds.) ACM SIGMM International Conference on Multimedia Information Retrieval, 30-31 October 2008, Vancouver.

View at publisher


There is an increasing need for online news aggregation and visualization. Commercial systems, such as Google News and, have successfully launched a portal aiming at providing an aggregated view of the top news events at a given time. However, these systems, as well as previous research projects, lack the ability to personalize events according to the user’s need. Furthermore, users increasingly prefer to see multiple types of media to be presented when they follow a particular event of interest. In this paper, we describe a novel framework to allow the aggregation of online sources for text articles, images, videos and TV news into news stories, while the visualization enables the users to browse and select the news events based on semantic information. The experimental results have indicated some promising results.

Impact and interest:

2 citations in Scopus
Search Google Scholar™

Citation counts are sourced monthly from Scopus and Web of Science® citation databases.

These databases contain citations from different subsets of available publications and different time periods and thus the citation count from each is usually different. Some works are not in either database and no count is displayed. Scopus includes citations from articles published in 1996 onwards, and Web of Science® generally from 1980 onwards.

Citations counts from the Google Scholar™ indexing service can be viewed at the linked Google Scholar™ search.

Full-text downloads:

375 since deposited on 18 Feb 2009
18 in the past twelve months

Full-text downloads displays the total number of times this work’s files (e.g., a PDF) have been downloaded from QUT ePrints as well as the number of downloads in the previous 365 days. The count includes downloads for all files if a work has more than one.

ID Code: 17956
Item Type: Conference Paper
Refereed: Yes
DOI: 10.1145/1460096.1460157
ISBN: 978-1-60558-312-9
Divisions: Past > QUT Faculties & Divisions > Faculty of Science and Technology
Copyright Owner: Copyright ACM
Copyright Statement: This is a digitized copy derived from an ACM-copyrighted work. ACM did not prepare this copy and does not guarantee that it is an accurate copy of the originally published work.
Deposited On: 18 Feb 2009 00:33
Last Modified: 29 Feb 2012 13:50

Export: EndNote | Dublin Core | BibTeX

Repository Staff Only: item control page