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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Wei He Runsheng Li Zhenyu Wu Jun Hu Yu Liu |
| Copyright Year | 2012 |
| Description | Author affiliation: State Key Lab of Software Development Environment, Beihang University, Beijing, China (Wei He; Runsheng Li; Zhenyu Wu; Jun Hu; Yu Liu) |
| Abstract | In this paper, we aim to propose an new approach to automatically generate text and photo overviews for landmarks, using the vast quantity of geo-tagged photos from photo sharing websites such as Flickr. To that end we first cluster a large-scale geo-tagged web photo collections into groups by location. And next, we make our focus on analyzing tags(user-entered text labels associated with a photo) and develop an TF-IDF like approach to evaluate the representativeness of a tag within group. To provide a more friendly and comprehensive overview, we try to mine topic patterns in each group. So we propose a clustering method among tags to discover some meaningful topics. The text overviews are generated based on tag's representativeness and topics discovered, and the photo overviews generating is simply a retrieval work according to the overview tags generated. We perform evaluations over 530,123 real geo-tagged photos taken in Beijing from Flickr and The experiment shows our approach can obtain a better result than state-of-the-art method. |
| Starting Page | 2644 |
| Ending Page | 2649 |
| File Size | 448299 |
| Page Count | 6 |
| File Format | |
| ISBN | 9781467317139 |
| e-ISBN | 9781467317146 |
| e-ISBN | 9781467317122 |
| DOI | 10.1109/ICSMC.2012.6378146 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2012-10-14 |
| Publisher Place | Korea (South) |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Clustering algorithms Asia Educational institutions Clustering methods Cities and towns Bandwidth Google tf-idf geotagged tag photo topic location |
| Content Type | Text |
| Resource Type | Article |
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