ABSTRACT: Based on clustering algorithm Affinity Propagation (AP) I present this paper a semisupervised text clustering algorithm, called Seeds Affinity Propagation (SAP). There are two main contributions in my approach: 1) a similarity metric that captures the structural information of texts, and 2) seed construction method to improve the semisupervised clustering process. To study the perform...

A nonparametric video retrieval and frame classification systm that uses affinity propagation algorithm is proposed. The main goal of the proposed system is to develop "tiny video" that achieves high video compression rates while retaining the overall visual appearance of video. The proposed video retrieval system utilizes the strengths of affinity propagation algorithm that uses exem...

Rapid developments in the biomedical sciences have increased the demand for automatic clustering of biomedical publications. In contrast to current approaches to text clustering, which focus exclusively on the contents of abstracts, a novel method is proposed for clustering and analysis of complete biomedical article texts. To reduce dimensionality, Cosine Coefficient is used on a sub-space of ...

We present a novel method called Time Series Affinity Propagation (TSAP) for inferring regulatory states and trajectories from time series genomic data. This method builds on the Affinity Propagation method of Frey and Dueck [10]. TSAP incorporates temporal constraints to more accurately model the dynamic nature of underlying biological mechanisms. We first apply TSAP to synthetic data and demo...

A nonparametric video retrieval and frame classification systm that uses affinity propagation algorithm is proposed. The main goal of the proposed system is to develop "tiny video" that achieves high video compression rates while retaining the overall visual appearance of video. The proposed video retrieval system utilizes the strengths of affinity propagation algorithm that uses exem...

When data are acquired at multiple points in time, evolutionary clustering can provide insights into cluster evolution and changes in cluster memberships while enabling performance superior to that obtained by independently clustering data collected at different time points. Existing evolutionary clustering methods typically require additional steps before and after the clustering stage to appr...

In many applications, the pairwise constraint is a kind of weaker supervisory information which can be collected easily. The constraint propagation has been proved to be a success of exploiting such side-information. In recent years, some methods of multi-view constraint propagation have been proposed. However, the problem of reasonably fusing different views remains unaddressed. In this paper,...

Image-guided depth completion aims to generate dense maps with sparse measurements and corresponding RGB images. Currently, spatial propagation networks (SPNs) are the most popular affinity-based methods in completion, but they still suffer from representation limitation of fixed affinity over smoothing during iterations. Our solution is estimate independent matrices each SPN iteration, it over...