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Proceedings ArticleDOI

Topickr: flickr groups and users reloaded

TLDR
This work presents a topic-based approach to represent Flickr users and groups and demonstrates it with a web application, Topickr, that allows similarity based exploration of Flickr entities using their topic- based representation, learned in an unsupervised manner.
Abstract
With the increased presence of digital imaging devices there also came an explosion in the amount of multimedia content available online. Users have transformed from passive consumers of media into content creators. Flickr.com is such an example of an online community, with over 2 billion photos (and more recently, videos as well), most of which are publicly available. The user interaction with the system also provides a plethora of metadata associated with this content, and in particular tags. One very important aspect in Flickr is the ability of users to organize in self-managed communities called groups. Although users and groups are conceptually different, in practice they can be represented in the same way: a bag-of-tags, which is amenable for probabilistic topic modeling. We present a topic-based approach to represent Flickr users and groups and demonstrate it with a web application, Topickr, that allows similarity based exploration of Flickr entities using their topic-based representation, learned in an unsupervised manner.

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Citations
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Journal ArticleDOI

Which photo groups should I choose? A comparative study of recommendation algorithms in Flickr

TL;DR: This paper designs and compares seven Flickr group recommendation models and suggests that model-based approaches are beneficial compared with memory-based approach in terms of top-k recommendation metric, and incorporating tags in the recommendation algorithms leads to an improvement of precision on the top 2% performance.
Proceedings ArticleDOI

Modeling social strength in social media community via kernel-based learning

TL;DR: A kernel-based learning to rank framework for inferring the social strength of Flickr users, which involves two learning stages and is able to conduct collaborative recommendation and collective classification.
Journal ArticleDOI

Recommending Flickr groups with social topic model

TL;DR: This paper presents a probabilistic latent topic model to model Flickr groups in an integrated framework, expecting to jointly discover the latent interests for users and groups and simultaneously learn the recommendation function.
Proceedings ArticleDOI

Flickr hypergroups

TL;DR: A novel approach to group searching through hypergroup discovery is proposed, starting from roughly 11,000 Flickr groups' content and membership information, and it is shown that hypergroups found are generally consistent and can be described through topic-based and similarity-based measures.
Proceedings ArticleDOI

Flickr group recommendation based on tensor decomposition

TL;DR: A tensor decomposition-based group recommendation model to suggest groups to users which can help tackle the problem of huge volume of groups in Flickr.
References
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Journal ArticleDOI

Unsupervised Learning by Probabilistic Latent Semantic Analysis

TL;DR: This paper proposes to make use of a temperature controlled version of the Expectation Maximization algorithm for model fitting, which has shown excellent performance in practice, and results in a more principled approach with a solid foundation in statistical inference.
Proceedings ArticleDOI

The author-topic model for authors and documents

TL;DR: The author-topic model is introduced, a generative model for documents that extends Latent Dirichlet Allocation to include authorship information, and applications to computing similarity between authors and entropy of author output are demonstrated.
Proceedings ArticleDOI

HT06, tagging paper, taxonomy, Flickr, academic article, to read

TL;DR: A model of tagging systems, specifically in the context of web-based systems, is offered to help illustrate the possible benefits of these tools and a simple taxonomy of incentives and contribution models is provided to inform potential evaluative frameworks.
Proceedings ArticleDOI

Why we tag: motivations for annotation in mobile and online media

TL;DR: The incentives for annotation in Flickr, a popular web-based photo-sharing system, and ZoneTag, a cameraphone photo capture and annotation tool that uploads images to Flickr are investigated to offer a taxonomy of motivations for annotation along two dimensions (sociality and function).
Proceedings ArticleDOI

How flickr helps us make sense of the world: context and content in community-contributed media collections

TL;DR: A location-tag-vision-based approach to retrieving images of geography-related landmarks and features from the Flickr dataset is demonstrated, suggesting that community-contributed media and annotation can enhance and improve access to multimedia resources - and the understanding of the world.
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