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|dc.contributor.author||Sowmya, Kamath S.||-|
|dc.identifier.citation||2015 IEEE International Conference on Electronics, Computing and Communication Technologies, CONECCT 2015, 2016, Vol., , pp.-||en_US|
|dc.description.abstract||Geo-tagged photos enable people to share their personal experiences while visiting various vacation spots through image sharing social networks like Flickr. The geo-tag information offers a wealth of information for capturing additional information on traveler behavior, trends, opinions and interests. In this paper, we propose a landmark discovery system that aims to discover popular tourist attractions in a city by assuming that the popularity of a tourist attraction is positively dependent on the visitor statistics and also the amount of tourist uploaded photos clicked on site. It is a known fact that places with lots of geo-tagged photos uploaded to Flickr are visited more often by social-media savvy tourists, who plan their trip based on others' experiences. We propose to build a system that identifies the most popular tourist places in a particular city by using geo-tagged photos collected from Flickr and recommend the same to the user. In this paper, we present the methodology of spatially clustering the geo-tagged images and present an analysis of algorithm performance in identifying landmarks and their popularity. � 2015 IEEE.||en_US|
|dc.title||A spatial clustering approach for efficient landmark discovery using geo-tagged photos||en_US|
|Appears in Collections:||2. Conference Papers|
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