TY - GEN
T1 - NewsStand
T2 - 16th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, ACM GIS 2008
AU - Teitler, Benjamin E.
AU - Lieberman, Michael D.
AU - Panozzo, Daniele
AU - Sankaranarayanan, Jagan
AU - Samet, Hanan
AU - Sperling, Jon
PY - 2008
Y1 - 2008
N2 - News articles contain a wealth of implicit geographic content that if exposed to readers improves understanding of today's news. However, most articles are not explicitly geotagged with their geographic content, and few news aggregation systems expose this content to users. A new system named NewsStand is presented that collects, analyzes, and displays news stories in a map interface, thus leveraging on their implicit geographic content. NewsStand monitors RSS feeds from thousands of online news sources and retrieves articles within minutes of publication. It then extracts geographic content from articles using a custom-built geotagger, and groups articles into story clusters using a fast online clustering algorithm. By panning and zooming in NewsStand's map interface, users can retrieve stories based on both topical significance and geographic region, and see substantially different stories depending on position and zoom level.
AB - News articles contain a wealth of implicit geographic content that if exposed to readers improves understanding of today's news. However, most articles are not explicitly geotagged with their geographic content, and few news aggregation systems expose this content to users. A new system named NewsStand is presented that collects, analyzes, and displays news stories in a map interface, thus leveraging on their implicit geographic content. NewsStand monitors RSS feeds from thousands of online news sources and retrieves articles within minutes of publication. It then extracts geographic content from articles using a custom-built geotagger, and groups articles into story clusters using a fast online clustering algorithm. By panning and zooming in NewsStand's map interface, users can retrieve stories based on both topical significance and geographic region, and see substantially different stories depending on position and zoom level.
KW - Clustering
KW - Geotagging
KW - Knowledge discovery
KW - Text mining
UR - http://www.scopus.com/inward/record.url?scp=70449730083&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=70449730083&partnerID=8YFLogxK
U2 - 10.1145/1463434.1463458
DO - 10.1145/1463434.1463458
M3 - Conference contribution
AN - SCOPUS:70449730083
SN - 9781605583235
T3 - GIS: Proceedings of the ACM International Symposium on Advances in Geographic Information Systems
SP - 144
EP - 153
BT - Proceedings of the 16th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, ACM GIS 2008
Y2 - 5 November 2008 through 7 November 2008
ER -