Results 241 to 250 of about 70,533 (290)

Age-related differences in implicit temporal preparation. [PDF]

Front Psychol
Welhaf MS.
europepmc   +1 more source

Spectroscopy based analysis of rice residue driven by microbial decomposition and nitrogen management under zero till wheat in Northern India. [PDF]

Sci Rep
Khedwal RS, Singh J, Kalia A, Singh KB, Singh R, Singh I, Preet A.   +6 more
europepmc   +1 more source

A multi-centre, multi-device benchmark dataset for landmark-based comprehensive fetal biometry

Vece CD, Mao Z, Avisdris N, Dromey B, Napolitano R, Bashat DB, Vasconcelos F, Stoyanov D, Joskowicz L, Bano S.   +9 more
europepmc   +1 more source

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Message-driven FP-growth

Proceedings of the WICSA/ECSA 2012 Companion Volume, 2012
Frequent itemset mining finds frequently occurring itemsets in transactional data. This is applied to diverse problems such as decision support, selective marketing, financial forecast and medical diagnosis. The cloud, computation as an utility service, allows us to crunch large mining problems.
openaire   +3 more sources

An efficient parallel FP-Growth algorithm

2009 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery, 2009
FP-Growth algorithm recursively generates huge amounts of conditional pattern bases and conditional FP-trees when the dataset is huge. In such a case, both the memory usage and computational cost are expensive, such that, the FP-tree can not meet the memory requirement. In this work, we propose a novel parallel FP-Growth algorithm, which is designed to
Min Chen, XueDong Gao, HuiFei Li
openaire   +1 more source

Balanced parallel FP-Growth with MapReduce

2010 IEEE Youth Conference on Information, Computing and Telecommunications, 2010
Frequent itemset mining (FIM) plays an essential role in mining associations, correlations and many other important data mining tasks. Unfortunately, as the volume of dataset gets larger day by day, most of the FIM algorithms in literature become ineffective due to either too huge resource requirement or too much communication cost.
null Le Zhou, null Zhiyong Zhong, null Jin Chang, null Junjie Li, null Joshua Zhexue Huang, null Shengzhong Feng   +5 more
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Discovering drugs combination pattern using FP-growth algorithm

2017 4th International Conference on Electrical Engineering, Computer Science and Informatics (EECSI), 2017
A drug can be used to deal more than one diseases and to deal an illness often need a combination of more than one drugs. This paper present how to discover a pattern of a combination of medicines related to a diagnosis of diseases using FP-Growth one of frequent pattern mining algorithm.
Rini Anggrainingsih, Nach Rowi Khoirudin, Haryono Setiadi   +2 more
openaire   +1 more source

Hiding sequential patterns using FP growth technique

International Conference on Computer Networks and Information Technology, 2011
Data mining deals with discovering useful and unknown information from databases. Databases may contain some sensitive information. This information need to be hidden from outside world, i.e. when we extract useful information, sensitive information should not be leaked. To deal with such situation, privacy preservation data mining comes into play. The
F. Shahzad, S. Asghar
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FP GROWTH ALGORITHM MODELING FOR PRODUCT INVENTORY ANALYSIS

Proceeding of International Conference on Science, Health, And Technology, 2023
Pusaka Tani is a shop that provides agricultural needs such as fertilizers, rice seeds and plant medicines. Sales transactions at the Farmer's Library still use a manual system, namely by using notes as proof of sales transactions. The amount of data that accumulates results in less useful data.
Dwi Hartanti, Vihi Atina
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