Flickr users tag their personal pictures with a variety of keywords. Such annotations could provide genuine insights on salient aspects emerging from the personal experiences that have been captured in the picture, which range beyond the purely visual features, or the language-based associations. Mining the emergent semantic patterns of these complex open- ended large-scale bodies of uncoordinated annotations provided by humans is the goal of this chapter. This is achieved by means of distributional semantics, i.e. by relying on the idea that concepts that appear in similar contexts have similar meanings (e.g. LSA, Landauer, Dumais 1997). This chapter presents the Flickr Distributional Tagspace (FDT), a distributional semantic space built on Flickr tag co-occurrences, and evaluates it follows: 1) through a comparison between the semantic representations that it produces, and those that are obtained from speaker generated features norms collected in experimental setting , as well as with WordNet-based metrics of semantic similarity between words; 2) through a categorization task and a consequent cluster analysis. The results of the two studies suggest that FDT can deliver semantic representations that correlate with those that emerge from aggregations of features norms, and can cluster fairly homogeneous categories and subcategories of related concepts.
Bolognesi M (2016). Flickr® Distributional Tagspace: Evaluating the Semantic Spaces emerging from Flickr® Tags Distributions. New York : Routledge.
Flickr® Distributional Tagspace: Evaluating the Semantic Spaces emerging from Flickr® Tags Distributions
Bolognesi M
2016
Abstract
Flickr users tag their personal pictures with a variety of keywords. Such annotations could provide genuine insights on salient aspects emerging from the personal experiences that have been captured in the picture, which range beyond the purely visual features, or the language-based associations. Mining the emergent semantic patterns of these complex open- ended large-scale bodies of uncoordinated annotations provided by humans is the goal of this chapter. This is achieved by means of distributional semantics, i.e. by relying on the idea that concepts that appear in similar contexts have similar meanings (e.g. LSA, Landauer, Dumais 1997). This chapter presents the Flickr Distributional Tagspace (FDT), a distributional semantic space built on Flickr tag co-occurrences, and evaluates it follows: 1) through a comparison between the semantic representations that it produces, and those that are obtained from speaker generated features norms collected in experimental setting , as well as with WordNet-based metrics of semantic similarity between words; 2) through a categorization task and a consequent cluster analysis. The results of the two studies suggest that FDT can deliver semantic representations that correlate with those that emerge from aggregations of features norms, and can cluster fairly homogeneous categories and subcategories of related concepts.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.