...
首页> 外文期刊>Robotics and Machine Learning >Studies from University of Calgary, Department of Computer Science Yield New Data on Data Structures
【24h】

Studies from University of Calgary, Department of Computer Science Yield New Data on Data Structures

机译:卡尔加里大学计算机科学系的研究产生了数据结构的新数据

获取原文
获取原文并翻译 | 示例
   

获取外文期刊封面封底 >>

       

摘要

Research findings, 'A bounded and adaptive memory-based approach to mine frequent patterns fromnvery large databases,' are discussed in a new report. "Most of the existing methods to solve the problemnof association rules mining (ARM) rely on special data structures to project the database (either totally ornpartially) in the primary memory. Traditionally, these data structures reside in the main memory and relynon the existing paging mechanism of the virtual memory manager (VMM) to handle the storage problemnwhen they go out of the primary memory," scientists in Calgary, Canada report.
机译:一份新的报告中讨论了研究成果“一种基于限制和自适应内存的方法来从多个大型数据库中挖掘频繁模式”。 “解决关联规则挖掘(ARM)问题的大多数现有方法都依赖于特殊的数据结构来将数据库(全部或部分地)投影到主存储器中。传统上,这些数据结构驻留在主存储器中,并且不依赖于现有的分页“虚拟内存管理器(VMM)用来处理存储不足时的存储机制”,加拿大卡尔加里的科学家报告说。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号