As the rapid development of the internet, we can collect more and more information. it also means we need the abitily to search the information which really useful to us from the amount of information quickly. Automatic summarization is useful to us for handling the huge amount of text information in the Web. This paper proposes a Chinese summarization method based on Affinity Propagation(AP)cl...

We propose a new way of generating personalized single document summary by combining two complementary methods: collaborative filtering for tag recommendation and graph-based affinity propagation. The proposed method, named by Collaborative Summarization, consists of two steps iteratively repeated until convergence. In the first step, the possible tags of one user on a new document are predicte...

Clustering is the process of subdividing an input data set into a desired number of subgroups so that members of the same subgroup are similar and members of different subgroups have diverse properties. Many heuristic algorithms have been applied to the clustering problem, which is known to be NP Hard. This paper represents a frame work for clustering on image data. The objective of the frame w...

In diesem Artikel wird anhand des Clusteralgorithmus Affinity Propagation (AP) eine Bibliothek bestehend aus algorithmischen Skeletten vorgestellt, mit deren Hilfe Berechnungen auf die GPU verlagert werden können. Nach einer kurzen Beschreibung von AP wird eingehend auf die Implementierung der Bibliothek und deren Skelette eingegangen: Sowohl die abstrakten Bausteine als auch die konkrete Umset...

Affinity propagation (AP) algorithm, as a novel clustering method, does not require the users to specify the initial cluster centers in advance, which regards all data points as potential exemplars (cluster centers) equally and groups the clusters totally by the similar degree among the data points. But in many cases there exist some different intensive areas within the same data set, which mea...

Web queries tend to have multiple user intents. Automatically identifying query intents will benefit search result navigation, search result diversity and personalized search. This paper presents the HITSCIR system in NTCIR-9 subtopic mining task. Firstly, the system collects query intent candidates from multiple resources. Secondly, Affinity Propagation algorithm is applied for clustering thes...

Human action recognition using 3D skeletal data has become popular topic with the emergence of the cost-effective depth sensors, such as Microsoft Kinect. However, noisy joint position and speed variation between actors make action recognition from 3D joint positions difficult. To address these problems, this paper proposes a novel framework, called Enhanced Sequence Matching (ESM), to align an...

Exemplar based techniques such as affinity propagation [1] represent data in terms of typical exemplars. This has two benefits: (i) the resulting models are directly interpretable by humans since representative exemplars can be inspected in the same way as data points, (ii) the model can be applied to any dissimilarity measure including non-Euclidean or non-metric settings. Most exemplar based ...

In this paper, we detail our participation in two subtasks: subtopic mining and document ranking of the NTCIR-11 IMine task. In the subtopic mining subtask, to discover the latent hierarchy among query-like strings, our key idea is to structurally parse query-like strings by characterizing pairwise dependency in the bag-of-units perspective. Then the clustering algorithm (i.e., affinity propaga...

Human cortical folding pattern has been studied for decades. This paper proposes a gyrus scale folding pattern analysis technique via cortical surface profiling. Firstly, we sample the cortical surface into 2D profiles and model them using power function. This step provides both the flexibility of representing arbitrary shape by profiling and the compactness of representing shape by parametric ...