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ICWSM
2009

A Categorical Model for Discovering Latent Structure in Social Annotations

8 years 9 months ago
A Categorical Model for Discovering Latent Structure in Social Annotations
The advent of social tagging systems has enabled a new community-based view of the Web in which objects like images, videos, and Web pages are annotated by thousands of users. Understanding the emergent semantics inherent in the socially-generated collection of annotations has important research implications for information discovery and knowledge sharing. To this end, we propose a novel probabilistic generative model for discovering latent structure in large-scale social annotations. The generative model identifies latent community-based "categories" of interest that can be used to group semantically-related tags and to augment traditional content-based information search and discovery. We illustrate the proposed approach over large collections of Web objects annotated by the Flickr and Delicious communities. Additionally, we show how to integrate the annotation-based categorical model with traditional content-based approaches for the effective focused discovery and explora...
Said Kashoob, James Caverlee, Ying Ding
Added 19 Feb 2011
Updated 19 Feb 2011
Type Journal
Year 2009
Where ICWSM
Authors Said Kashoob, James Caverlee, Ying Ding
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