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摘要翻译：
孟加拉字母有大量的字母，因此使用孟加拉键盘打字比较复杂。建议的键盘将最大限度地提高操作者的速度，因为他们可以用双手平行打字。本文采用数据挖掘中的关联规则对键盘中的孟加拉文字进行分布。分析了从数据仓库中提取的专著、有向图和三向图数据的频率，并利用数据挖掘中的关联规则对版面中的孟加拉文字进行了分布。在多个数据上的实验结果表明了该方法的有效性和较好的性能。本文提出了一种最优的Bangla键盘布局，该布局将负载平均分配在双手上，以实现最大的轻松和最小的努力。
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英文标题：
《The Most Advantageous Bangla Keyboard Layout Using Data Mining Technique》
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作者：
Abdul Kadar Muhammad Masum, Mohammad Mahadi Hassan, and S. M.
Kamruzzaman
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最新提交年份：
2010
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分类信息：
一级分类：Computer Science 计算机科学
二级分类：Artificial Intelligence 人工智能
分类描述：Covers all areas of AI except Vision, Robotics, Machine Learning, Multiagent Systems, and Computation and Language (Natural Language Processing), which have separate subject areas. In particular, includes Expert Systems, Theorem Proving (although this may overlap with Logic in Computer Science), Knowledge Representation, Planning, and Uncertainty in AI. Roughly includes material in ACM Subject Classes I.2.0, I.2.1, I.2.3, I.2.4, I.2.8, and I.2.11.
涵盖了人工智能的所有领域，除了视觉、机器人、机器学习、多智能体系统以及计算和语言（自然语言处理），这些领域有独立的学科领域。特别地，包括专家系统，定理证明（尽管这可能与计算机科学中的逻辑重叠），知识表示，规划，和人工智能中的不确定性。大致包括ACM学科类I.2.0、I.2.1、I.2.3、I.2.4、I.2.8和I.2.11中的材料。
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英文摘要：
Bangla alphabet has a large number of letters, for this it is complicated to type faster using Bangla keyboard. The proposed keyboard will maximize the speed of operator as they can type with both hands parallel. Association rule of data mining to distribute the Bangla characters in the keyboard is used here. The frequencies of data consisting of monograph, digraph and trigraph are analyzed, which are derived from data wire-house, and then used association rule of data mining to distribute the Bangla characters in the layout. Experimental results on several data show the effectiveness of the proposed approach with better performance. This paper presents an optimal Bangla Keyboard Layout, which distributes the load equally on both hands so that maximizing the ease and minimizing the effort.
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PDF链接：
https://arxiv.org/pdf/1009.5048
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