Results 71 to 80 of about 3,318,937 (295)
In pursuit of efficient frequent pattern mining in data streams
, 2017 碩士資料串流探勘(Data stream mining)是現今大數據(Big data)領域的研究主題之一。資料串流指的是日常生活中隨著時間不斷產生的大量資料。例如：每個人上網的點擊串流、感測器產生的資料、購物資料、網路流量資料…等。這些資料串流中隱含著許多有價值的資訊，利用資料探勘(Data mining)的技術，可以分析出針對不同應用之下所需要的結果，最後做出更佳的決策。在資料探勘的領域中，其中有一個主題是頻繁樣式探勘(Frequent pattern mining ...
凃耘昇;Tu, Yun-Sheng
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Entropy‐Driven Design of Low‐Melting‐Point Alloys via Compositionally Complex Strategy
Advanced Engineering Materials, EarlyView.Conventional low‐melting‐point alloys (LMPAs) are limited by a narrow compositional space and inherent property trade‐offs. This review presents an entropy‐driven design strategy that overcomes these limitations, ushering in a new class of low‐melting‐point compositionally complex alloys (LMCCAs).
Yinghui Shang +6 more
wiley +1 more source
Fast Single Pbase Algoritbm for Utility Mining in Big Data
Dianxin kexue, 2015 Most of the latest works on utility mining generates a huge number of candidates in dealing with big data,which suffers from the scalability issue.Some work does not generate candidates,but suffers from the efficiency issue due to lack of strong pruning ...
Junqiang Liu +3 more
doaj +2 more sources
Algorithms for Extracting Frequent Episodes in the Process of Temporal Data Mining [PDF]
Informatică economică, 2010 An important aspect in the data mining process is the discovery of patterns having a great influence on the studied problem. The purpose of this paper is to study the frequent episodes data mining through the use of parallel pattern discovery algorithms.
Alexandru PIRJAN
doaj
Enabling Far-Edge Analytics: Performance Profiling of Frequent Pattern Mining Algorithms
IEEE Access, 2017 Far-edge analytics refers to the enablement of data mining algorithms in far-edge mobile devices that are part of mobile edge cloud computing (MECC) systems.
Khubaib Amjad Alam +2 more
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Advanced Engineering Materials, EarlyView.This article explores the transformative potential of symbolic artificial intelligence (AI) in the field of materials science, particularly in leveraging experimental data. The article presents several symbolic AI models and discusses their applications in materials science.
Ahmed Amrani +7 more
wiley +1 more source
Efficient Algorithms for Mining Frequent Patterns from Sparse and Dense Databases
Journal of Intelligent Systems, 2015 In this article, we present a new approach for frequent pattern mining (FPM) that runs fast for both sparse and dense databases. Two algorithms, FEM and DFEM, based on our approach are also introduced.
Vu Lan, Alaghband Gita
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RP-Miner: a relaxed prune algorithm for frequent similar pattern mining [PDF]
, 2011 Most of the current algorithms for mining frequent patterns assume that two object subdescriptions are similar if they are equal, but in many real-world problems some other ways to evaluate the similarity are used. Recently, three algorithms (ObjectMiner,
José Francisco Martínez Trinidad +2 more
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A Multi‐Scale Machine Learning Framework for the Inverse Design of High Entropy Alloys
Advanced Engineering Materials, EarlyView.High‐entropy alloys offer vast potential for various applications, including electrocatalysis; however, their compositional complexity challenges conventional screening. We introduce an inverse‐design framework combining two neural networks to determine optimal compositions and reconstruct nanoparticle geometry from targeted properties and conventional
Mikael Takoutsin +14 more
wiley +1 more source
A Novel Coverage Pattern Mining Method for Unordered Tree
ITM Web of Conferences, 2017 Unordered tree is widely used for semi-structured data modeling, coverage pattern mining on it has benefit for finding frequent subtrees without redundant information, so that improve the efficiency of subsequent knowledge discovering. A coverage pattern
Xia Ying, Li Hong-Xu
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