Development of Parallel Knowledge Acquisition System

并行知识获取系统的开发

• 批准号: 06558047
• 负责人: MIYANO Satoru
• 金额: $ 11.07万
• 依托单位: The University of Tokyo (1996)Kyushu University (1994-1995)
• 依托单位国家: 日本
• 项目类别: Grant-in-Aid for Scientific Research (A)
• 财政年份: 1994
• 资助国家: 日本
• 起止时间: 1994 至 1996
• 项目状态: 已结题
• 来源: https://kaken.nii.ac.jp/grant/KAKENHI-PROJECT-06558047/
• 关键词: knowledge acquisition; learning algorithm; parallel processing; 並列計算

The ability of knowledge acquision has strong effects on the developments of various scientific and industrial activities. The quality of the knowledge and the efficiency of the knowledge acquisition procedure are keys to these activities. A group or society with the such knowledge acquisition ability in information processing activities may be promised a big advance.The knowledge acquision activity is regarded as an activity which can be done by only human beings. Recently, however, computational learning technologies and artificial intelligence is realizing information systems which can play the knowledge acquisition activity instead of human beings. This research project has attained the following items by the above technologies.1. Paradigm of parallel knowledge acquisition.2. Design and development of a parallel knowledge acquisition system based on the above paradigm.With this system, we have made several computational experiments on knowledge acqusition, especially for DNA and amino acid sequences. The results were very successful. It is scheduled that this system will be open to publich via Human Genome Center of the University of Tokyo.

知识获取能力对各种科学和工业活动的发展有很强的影响。知识的质量和知识获取程序的效率是这些活动的关键。在信息处理活动中具有这种知识获取能力的群体或社会可能会有很大的进步。知识获取活动被认为是只有人类才能完成的活动。然而，近年来，计算学习技术和人工智能正在实现可以代替人类进行知识获取活动的信息系统。本研究项目通过以上技术实现了以下几个方面的成果。并行知识获取的范式。设计并开发了一个基于上述范型的并行知识获取系统，利用该系统对知识获取进行了多次计算实验，特别是对DNA和氨基酸序列的知识获取进行了实验。结果非常成功。按照计划，该系统将通过东京大学人类基因组中心向公众开放。

项目成果

宮野 悟: "ゲノムデータからの知識発見" 情報処理. 37. 935-940 (1996)

Satoru Miyano：“从基因组数据中发现知识”信息处理 37. 935-940 (1996)。

Arikawa, S.and Richter, M.(Eds.): "Algorithmic Learning Theory" New Generation Computing. 15, No. 1. 140 (1996)

Arikawa, S. 和 Richter, M.（编）：“算法学习理论”新一代计算。

Furukawa,N.: "HAKKE:a mutlti-strategy prediction system for sequences" Proc.7th Workshop on Genome Informatics,Universal Academy Press. 98-107 (1996)

Furukawa,N.：“HAKKE：序列的多策略预测系统”Proc.7th 基因组信息学研讨会，环球学院出版社。

M.Karpinski: "Pattern matching for strings with short descriptions" Lecture Notes in Computer Science. 937. 129-144 (1995)

M.Karpinski：“带有简短描述的字符串的模式匹配”计算机科学讲义。

S.Shimozono: "Knowledge acquisition from amino acid sequences by machine learning system BONSAI" 情報処理学会論文誌. 35. 2009-2018 (1994)

S.Shimozono：“通过机器学习系统 BONSAI 从氨基酸序列中获取知识”日本信息处理学会汇刊 35. 2009-2018 (1994)。