| Title |
A threefold similarity analysis of crowdsourcing feeds |
| ID_Doc |
44012 |
| Authors |
Liu, KX; Motta, G; You, LL; Ma, TY |
| Title |
A threefold similarity analysis of crowdsourcing feeds |
| Year |
2015 |
| Published |
|
| DOI |
10.1109/ICSS.2015.14 |
| Abstract |
Crowdsourcing is a valuable social sensing for the smarter city. We present an approach for classifying crowdsourced feeds from a threefold point of view, namely image, text, and geography. The main idea is to extract feeds within a specific geographic range, and then analyze similarity of image color and text semantic. The approach enables to identify feeds that report the same issue, hence filtering redundant information. Based on proved methods and algorithms, such approach has been implemented in a software application, called CITY FEED, that is used by the Municipality of Pavia. |
| Author Keywords |
Crowdsourcing; Smart city; Image similarity analysis; Text similarity analysis |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Conference Proceedings Citation Index - Science (CPCI-S) |
| EID |
WOS:000380433800017 |
| WoS Category |
Computer Science, Interdisciplinary Applications |
| Research Area |
Computer Science |
| PDF |
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