Paper Info
Title
Tagging space from information extraction and popularity of points of interest
Abstract
This paper is about automatic tagging of urban areas considering its constituent Points of Interest. First, our approach geographically clusters places that offer similar services in the same generic category (e.g. Food & Dining; Entertainment & Arts) in order to identify specialized zones in the urban context. Then, these places are analysed and tagged from available information sources on the Web using KUSCO [2,3] and finally the most relevant tags are chosen considering not only the place itself but also its popularity in social networks. We present some experiments in the greater metropolitan area of Boston.
Year
DOI
Venue
2011
10.1007/978-3-642-25167-2_13
AMI
Keywords
Field
DocType
relevant tag,greater metropolitan area,approach geographically clusters place,automatic tagging,tagging space,urban context,urban area,constituent points,similar service,available information source,generic category,information extraction
World Wide Web,Web mining,Social network,Entertainment,Computer science,Popularity,Context awareness,Information extraction,Point of interest,Metropolitan area
Conference
Volume
ISSN
Citations 
7040
0302-9743
2
PageRank 
References 
Authors
0.40
14
3
Name
Order
Citations
PageRank
Ana O. Alves1388.04
Filipe Rodrigues2978.80
Francisco C. Pereira333133.07