Exploiting Flickr Tags and Groups for Finding Landmark Photos

Abbasi, Rabeeh Ayaz; Chernov, Sergey; Nejdl, Wolfgang; Paiu, Raluca; Staab, Steffen

doi:10.1007/978-3-642-00958-7_62

Cited by 44 publications

(37 citation statements)

References 3 publications

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“…Their approach is embedded into a recommendation method for photo tagging, similar to [19] who analyze different aspects and contexts of the tag and image data. Abbasi et al present a method to identify landmark photos using tags and social Flickr groups [20]. They apply group information and statistical preprocessing of the tags for obtaining interesting landmark photos.…”

Section: Related Workmentioning

confidence: 99%

Describing Locations Using Tags and Images: Explorative Pattern Mining in Social Media

Lemmerich

Atzmueller

2012

Modeling and Mining Ubiquitous Social Media

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Abstract. This paper presents an approach for explorative pattern mining in social media for describing image media based on tagging information and collaborative geo-reference annotations. We utilize pattern mining techniques for obtaining sets of tags that are specific for the specified point, landmark, or region of interest. Next, we show how these candidate patterns can be presented and visualized for interactive exploration using a combination of general pattern mining visualizations and views specialized on geo-referenced tagging data. We present a case study using publicly available data from the Flickr photo sharing platform.

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Section: Related Workmentioning

confidence: 99%

Describing Locations Using Tags and Images: Explorative Pattern Mining in Social Media

Lemmerich

Atzmueller

2012

Modeling and Mining Ubiquitous Social Media

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“…They use methods inspired by burst-analysis techniques and propose scale-structure identification. Abbasi et al [1] identify landmarks using tags, Flickr groups without exploiting geospatial information. They use SVM classifiers trained on thematical Flickr groups, in order to find relevant landmarkrelated tags.…”

Section: B Using Only Textual Metadatamentioning

confidence: 99%

Placing User-Generated Photo Metadata on a Map

Spyrou

Mylonas

2011

2011 Sixth International Workshop on Semantic Media Adaptation and Personalization

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Abstract-In this paper we analyze large user photo collections from Flickr in order to select the most appropriate tags to describe a geographical area. We cluster photos based on their latitude and longitude and divide large areas into smaller clusters, which we will refer to as "geo-clusters". Geo-clusters have a fixed size and are able to overlap. They do not cover the entire area of interest, omitting parts where no single photo has been geo-tagged at. Within each geo-cluster we analyze all collected textual metadata i.e. the user selected tags of the photos it contains. We are then able to rank them and select the most appropriate that are able to describe landmarks and other places of interest that are contained within. Finally we place these tags on a map to help users to intuitevely understand places of interest/visual content at a glance.

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“…uses an internet connection over WLAN or GSM, dependent on their availability. 5 http://en.wikipedia.org/wiki/Android …”

Section: A Mobile Clientmentioning

confidence: 99%

“…We call the task of automatic selection of representative landmarks for a given location the landmark finding problem. Recent research on landmark finding was focused on creating landmark photo summaries [1], [2], [3], [4], [5]. Some working prototypes for landmark finding are available online, for example, in the World Explorer application 1 a user can enter a location name and browse through the landmark related tags and the corresponding photos.…”

Section: Introductionmentioning

confidence: 99%