A High-Efficiency Querying Algorithm for Multi-Attribute Text String Identifiers

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Title:	A High-Efficiency Querying Algorithm for Multi-Attribute Text String Identifiers
Authors:	馬恆 ma, heng
Contributors:	工業管理學系 Industrial Management
Keywords:	多属性分类；小脑模型控制器；布隆筛检 Multi-attribute;CMAC;Bloom Filter
Date:	2010
Issue Date:	2014-06-27 00:10:55 (UTC+8)
Abstract:	本研究重点着重于具多重属性之大量数据高效能查询算法，透过算法实现压缩数据、快速查询等功能。高效能的查询模式如Bloom filter、CMAC，主要原理是将原始数据转换为低维度型态以利提高运算效率。然而此类型查询模式原始的设计重点在于简单的二元查询，如存在属性。对于多重属性查询必须设计出更复杂的结构，效能也相对地降低。本研究结合Bloom Filter 及CMAC 神经网络，开发多属性编码及反馈修正训练算法，实现多属性查询架构。本研究将以台湾自用车牌作为训练样本，实现多属性编码、数据压缩及快速搜寻等功能。 This research focuses on developing a high-speed query algorithm for multi-attribute large-volume data, in which data compression and fast querying can be simultaneously achieved. In the past decade, this type of problem is usually resolved by storing the
Appears in Collections:	[Industrial Management] Seminar Papers

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