使用可重构设备的分层聚类

2006 14th Annual IEEE Symposium on Field-Programmable Custom Computing Machines Pub Date : 2006-04-24 DOI:10.1109/FCCM.2006.49

Shobana Padmanabhan, Moshe Looks, Dan Legorreta, Young-Hee Cho, J. Lockwood

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引用次数: 1

摘要

非分层k-均值算法已经在硬件上实现，最常用于图像聚类。在这里，我们主要关注基于文档相似度的文本文档的分层聚类。据我们所知，这是第一次提出为硬件实现设计的分层聚类算法，我们的是第一个硬件加速实现

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Hierarchical Clustering using Reconfigurable Devices

Non-hierarchical k-means algorithms have been implemented in hardware, most frequently for image clustering. Here, we focus on hierarchical clustering of text documents based on document similarity. To our knowledge, this is the first work to present a hierarchical clustering algorithm designed for hardware implementation and ours is the first hardware-accelerated implementation

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2006 14th Annual IEEE Symposium on Field-Programmable Custom Computing Machines

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