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» K-medoid-style Clustering Algorithms for Supervised Summary ...
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MM
2009
ACM
197views Multimedia» more  MM 2009»
14 years 2 months ago
Visual summaries of popular landmarks from community photo collections
We present a novel data-driven algorithm that leverages online image repositories such as Flickr for automatically generating tourist maps. Our hypothesis is that, given a large e...
Wei-Chao Chen, Agathe Battestini, Natasha Gelfand,...
DATAMINE
2006
157views more  DATAMINE 2006»
13 years 7 months ago
Data Clustering with Partial Supervision
Clustering with partial supervision finds its application in situations where data is neither entirely nor accurately labeled. This paper discusses a semisupervised clustering algo...
Abdelhamid Bouchachia, Witold Pedrycz
ECIR
2007
Springer
13 years 9 months ago
Hierarchical Browsing of Video Key Frames
We propose an innovative, general purpose, method to the selection and hierarchical representation of key frames of a video sequence for video summarization. It is able to create a...
Gianluigi Ciocca, Raimondo Schettini
KDD
2005
ACM
135views Data Mining» more  KDD 2005»
14 years 7 months ago
A hybrid unsupervised approach for document clustering
We propose a hybrid, unsupervised document clustering approach that combines a hierarchical clustering algorithm with Expectation Maximization. We developed several heuristics to ...
Mihai Surdeanu, Jordi Turmo, Alicia Ageno
ICPR
2010
IEEE
13 years 9 months ago
A Semi-Supervised Gaussian Mixture Model for Image Segmentation
In this paper, the results of a semi-supervised approach based on the Expectation-Maximisation algorithm for model-based clustering are presented. We show in this work that, if th...
Adolfo Martínez-Usó, F. Pla, Jose Martínez Soto...