Classifying tags using open content resources

Abstract

Tagging has emerged as a popular means to annotate on-line objects such as bookmarks, photos and videos. Tags vary in semantic meaning and can describe different aspects of a media object. Tags describe the content of the media as well as locations, dates, people and other associated meta-data. Being able to automatically classify tags into semantic categories allows us to understand better the way users annotate media objects and to build tools for viewing and browsing the media objects. In this paper we present a generic method for classifying tags using third party open content resources, such as Wikipedia and the Open Directory. Our method uses structural patterns that can be extracted from resource meta-data. We describe the implementation of our method on Wikipedia using WordNet categories as our classification schema and ground truth. Two structural patterns found in Wikipedia are used for training and classification: categories and templates. We apply our system to classifying Flickr tags. Compared to a WordNet baseline our method increases the coverage of the Flickr vocabulary by 115%. We can classify many important entities that are not covered by WordNet, such as, London Eye, Big Island, Ronaldinho, geocaching and wii.

Evaluating tag-based information access in image collections

“…[32] in order to search for images in the social tagging system Flickr. Although there are very few implementations of this type of interface, there is a great deal of current research in this area [29,38,8,7]. Similar to the tag cloud interface, this type of interface provides the user with the functionality to view the tags of the retrieved images in a visually appealing representation.…”

“…To decide which classification schema to utilize, we performed an extensive literature survey on currently available tag classification approaches [6,29,38,8,32,11]. In the end, we selected a In total, you will have to collect at least 10 pictures.…”

Linking User Generated Video Annotations to the Web of Data

“…For example, for pictures on Flickr.com [1,10] or videos on Youtube.com [3]. We believe that such automatic techniques could also be applied to link the user tags from Waisda?.…”

Tendencias en minería de datos de la Web

“…Research con el apoyo de otras instituciones comenzó pues permite no sólo optimizar el contenido actual de un sitio, sino también agregar nuevos contenidos 3,21 .…”