Research on parallel frequent pattern mining based on ontology and rules

机译：基于本体和规则的并行频繁模式挖掘研究

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After ten years of development, ILP has been widely used in the field of data mining, it is also a hot topic in today's research. But ILP also has many disadvantages, such as it is a NP problem, but also a stand-alone algorithm, so that when the data is large, the efficiency is relatively low. To solve this problem, in this article, the new expression of frequent patterns as well as the heterogeneous knowledge base depending on ontology and knowledge are proposed. Based on the above two improvements, the parallel implementation of ILP can be realized.

机译：经过十年的发展，ILP已广泛应用于数据挖掘领域，它也是当今研究的热点。但是ILP也有很多缺点，例如它是一个NP问题，而且还是一个独立的算法，因此当数据很大时，效率相对较低。为了解决这个问题，本文提出了频繁模式的新表达以及依赖于本体和知识的异构知识库。基于以上两个改进，可以实现ILP的并行实现。

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来源
《4th International Conference on Smart and Sustainable City》|2017年|1-5|共5页
会议地点 Shanghai(CN)
作者
Chenxi Yi; Ming Sun;
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作者单位

University of Electronic Science and Technology of China, Chendu, Sichuan, China;

University of Electronic Science and Technology of China, Chendu, Sichuan, China;

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会议组织
原文格式 PDF
正文语种 eng
中图分类
关键词
data mining; ontologies (artificial intelligence);

机译：数据挖掘;本体论（人工智能）;;

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3. A non-group parallel frequent pattern mining algorithm based on conditional patterns [J] . Zhe-jun KUANG, Hang ZHOU, Dong-dai ZHOU, 浙江大学学报（英文版）（C辑：计算机与电子） . 2019,第009期

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4. RESEARCH ON PARALLEL FREQUENT PATTERN MINING BASED ON ONTOLOGY AND RULES [C] . Chenxi YI, Ming Sun International Conference on Smart and Sustainable City . 2018

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5. New Approaches to Frequent and Incremental Frequent Pattern Mining [D] . Bicer, Mehmet. 2020

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6. Cross-Ontology Multi-level Association Rule Mining in the Gene Ontology [O] . Prashanti Manda, Seval Ozkan, Hui Wang, -1

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7. An Improvised Frequent Pattern Tree Based Association Rule Mining Technique with Mining Frequent Item Sets Algorithm and a Modified Header Table [O] . Agarwal, Vandit, Kushal, Mandhani, Kumar, Dr. Preetham 2015

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Research on parallel frequent pattern mining based on ontology and rules

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