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AN OVERVIEW OFASSOCIATION RULEMINING (ARM) ALGORITHMS FORMARKET BASKETANALYSIS (MBA)

Izang A.A, Goga Nicolae, Kuyoro Shade, Adetunji O
2017 Journal of research in engineering and applied sciences  
Association rule mining is an aspect of data mining that has revolutionized the area of predictive modelling paving way for data mining technique to become the recommended method for business owners to  ...  Data mining is a technique that has become a widely accepted procedure for organizations in sourcing for data and processing it for decision making.  ...  Support and confidence are the quality measures for association rules. The rule X=>Y with a given confidence c if c% of transactions in a given set of transactions B which contains X also contains Y.  ... 
doi:10.46565/jreas.2017.v02i04.001 fatcat:d5sdasxzkfg6bpjh7i2gmyvbny

Profiling relational data: a survey

Ziawasch Abedjan, Lukasz Golab, Felix Naumann
2015 The VLDB journal  
Among the simpler results are statistics, such as the number of null values and distinct values in a column, its data type, or the most frequent patterns of its data values.  ...  In addition, we review data profiling tools and systems from research and industry.  ...  Cfd and Cind discovery RuleMiner [28] Rule discovery Denial constraint discovery MADLib [71] Machine learning Simple column statistics Recent data quality tools are dependency-driven: Classical dependencies  ... 
doi:10.1007/s00778-015-0389-y fatcat:ojj7blyqgrfrhmyi7yjtn6stia

On Mining Instance-Centric Classification Rules

Jianyong Wang, G. Karypis
2006 IEEE Transactions on Knowledge and Data Engineering  
By introducing several novel search strategies and pruning methods into the rule discovery process, HARMONY also has high efficiency and good scalability.  ...  However, a fundamental limitation with many rule-based classifiers is that they find the rules by employing various heuristic methods to prune the search space, and select the rules based on the sequential  ...  However, the drawback of these approaches is that the number of initial rules is usually extremely large, significantly increasing the rule discovery and selection time.  ... 
doi:10.1109/tkde.2006.179 fatcat:jrgr2ez65raq3hfugbytclzqii

HARMONY: Efficiently Mining the Best Rules for Classification [chapter]

Jianyong Wang, George Karypis
2005 Proceedings of the 2005 SIAM International Conference on Data Mining  
Thus, the so-mined rules may not be the globally best rules for some instances in the training database.  ...  However, a fundamental limitation with many rule-based classifiers is that they find the classification rules in a coarsegrained manner.  ...  set of high-quality rules to be used for classification.  ... 
doi:10.1137/1.9781611972757.19 dblp:conf/sdm/WangK05 fatcat:2r67oy2ojvch7bv5j76wjbwx5q

Rule-Mining based classification: a benchmark study [article]

Margaux Luck, Nicolas Pallet, Cecilia Damon
2017 arXiv   pre-print
Our method first extracts rules (i.e., a conjunction of conditions about the values of a small number of input features) with our exhaustive rule-mining algorithm, then constructs a new feature space based  ...  This local feature space is easy interpretable by providing a human-understandable explanation under the explicit form of rules.  ...  Rule selection The rule selection step in our rule-mining algorithm proceeds in two stages. 1) It computes two measures of rule quality for each class of samples and selects rules on the basis of these  ... 
arXiv:1706.10199v1 fatcat:6ovflkbklzeidnvwobpyxoqrrq

A hybrid knowledge discovery system for oil spillage risks pattern classification

Udoinyang Godwin Inyang, Oluwole Charles Akinyokun
2014 Artificial intelligence research  
Rule pruning was performed with support (15%) and confidence (10%) minimum thresholds and antecedent-size of 3.  ...  NN training, validation and testing results yielded R > 0.839 in all cases indicating a strong linear relationship between each output and target data.  ...  Rules discovery, pruning and clustering Pattern discovery from the trained NN was performed in three stages using the modified Apriori Association rulemining algorithm.  ... 
doi:10.5430/air.v3n4p77 fatcat:x4p22qhdijel3jp7o6n5t3oasi

Urinary metabolic profiling of asymptomatic acute intermittent porphyria using a rule-mining-based algorithm

Margaux Luck, Caroline Schmitt, Neila Talbi, Laurent Gouya, Cédric Caradeuc, Hervé Puy, Gildas Bertho, Nicolas Pallet
2017 Metabolomics  
NMR spectrum buckets bins, corresponding to rules, were extracted and a logistic regression was trained.  ...  Methods Urine 1 H-NMR spectra of 73 patients with asymptomatic acute intermittent porphyria (aAIP) and familial or sporadic porphyria cutanea tarda (f/sPCT) were compared using a supervised rule-mining  ...  To identify the most discriminative rules, we used as a rule quality measure the z-score and the rule modality size.  ... 
doi:10.1007/s11306-017-1305-9 pmid:29416446 pmcid:PMC5794841 fatcat:lbetubj6ejbvtc3yr7b3xxiuom

An Improved HotSpot Algorithm and Its Application to Sandstorm Data in Inner Mongolia

Ren Qing-dao-er-ji, Rui Pang, Yue Chang
2020 Mathematical Problems in Engineering  
HotSpot is an algorithm that can directly mine association rules from real data.  ...  The results show that S_HotSpot algorithm can not only dynamically optimize the selection of support but also improve the quality of association rules as it is mining reasonable number of rules.  ...  Figure 4 : 4 HotSpot algorithm association rule-mining result. Figure 5 : 5 S_HotSpot mining results. Figure 6 : 6 HotSpot mining results. Figure 8 : 8 Wine-quality dataset part data.  ... 
doi:10.1155/2020/4020723 fatcat:hm4f7lkatjagvn6imf3ja2zboa

Interlinking SciGraph and DBpedia Datasets Using Link Discovery and Named Entity Recognition Techniques

Beyza Yaman, Michele Pasin, Markus Freudenberg, Michael Wagner
2019 International Conference on Language, Data, and Knowledge  
In order to do so we applied techniques that a) improve the identity resolution across these two sources using Link Discovery for the structured data (i.e. by annotating Springer Nature (SN) SciGraph entities  ...  applications which integrate data coming from disparate sources.  ...  Thus, as future work, we aim at: evaluating the quality of the produced data sets employing crowd-sourced user feedback to produce higher quality contents. using these preliminary results in order to set  ... 
doi:10.4230/oasics.ldk.2019.15 dblp:conf/ldk/YamanPF19 fatcat:rk7usirqz5frlkzgs3kqktzaki

How to Discover a Semantic Web Service by Knowing Its Functionality Parameters [article]

Golsa Heidari, Kamran Zamanifar, Naser Nematbakhsh, Farhad Mardookhi
2021 arXiv   pre-print
We use Universal Description, Discovery and Integration (UDDI) compliant web service registry.  ...  We wrote some rules for comparing two web services' parameters. Our algorithm compares the parameters of two web services' inputs/outputs by making a bipartite graph.  ...  I RULES OF COMPARING TWO PARAMETERS OF TWO WEB SERVICES Q Parameter Data Type Integer Real String Date Boolean R Parameter Integer 10 5 3 1 1 Real 10 10 1 0 1 String 7 7 10 8  ... 
arXiv:2107.02609v1 fatcat:ofcmucgkdzd6da5mtydxwnvo2u

Role of Data Mining in E-Payment systems [article]

Sabyasachi Pattanaik, Partha Pratim Ghosh
2010 arXiv   pre-print
Data Mining deals extracting hidden knowledge, unexpected pattern and new rules from large database.  ...  Trends in data mining include further efforts towards the exploration of new application areas and methods for handling complex data types, algorithm scalability, constraint based data mining and visualization  ...  To draw meaningful rules that has real business value, it may be worthwhile to select the statistically most significant set of rules from the large pool of rules generated by a rulemining algorithm.  ... 
arXiv:1003.1816v1 fatcat:zkanww4kkzbwfantksjx6rb5ia

Interactive visual exploration of association rules with rule-focusing methodology

Julien Blanchard, Fabrice Guillet, Henri Briand
2006 Knowledge and Information Systems  
On account of the enormous amounts of rules that can be produced by data mining algorithms, knowledge post-processing is a difficult stage in an association rule discovery process.  ...  In order to find relevant knowledge for decision-making, the user (a decision-maker specialized in the data studied) needs to rummage through the rules.  ...  It results from experimental data concerning the user's behavior in the discovery process.  ... 
doi:10.1007/s10115-006-0046-2 fatcat:xrpxujlhqngr3n3vjydyqnp23a

Synthesising Reinforcement Learning Policies Through Set-Valued Inductive Rule Learning [chapter]

Youri Coppens, Denis Steckelmacher, Catholijn M. Jonker, Ann Nowé
2021 Lecture Notes in Computer Science  
the core of our approach is the fact that an RL process does not just learn a policy, a mapping from states to actions, but also produces extra meta-information, such as action values indicating the quality  ...  We introduce a policy distilling algorithm, building on the CN2 rule mining algorithm, that distills the policy into a rule-based decision system.  ...  The goal of supervised rule induction is the discovery of rules that reflect relevant dependencies between classes and attribute values describing the given data [8] .  ... 
doi:10.1007/978-3-030-73959-1_15 fatcat:n433aoyl2jbgvf76jlgjnbyfwq

ICDE conference 2014 detailed author index

2014 2014 IEEE 30th International Conference on Data Engineering  
Systems 1222 RuleMiner: Data Quality Rules Discovery Parameswaran, Aditya 964 Crowd-Powered Find Algorithms Park, SeongJae 700 Scalable Serializable Snapshot Isolation for Multicore Systems  ...  Systems Meira Jr., Wagner 448 Complete Discovery of High-Quality Patterns in Large Numerical Tensors Meng, Cynthia 1254 KnowLife: A Knowledge Graph for Health and Life Sciences Menon, Prashanth  ... 
doi:10.1109/icde.2014.6816627 fatcat:bmnfkwqucfcmhet64s2o6ns5ky

Design of Intrusion Detection System using Fuzzy Class-Association Rule Mining based on Genetic Algorithm

Swati Dhopte, N. Z. Tarapore
2012 International Journal of Computer Applications  
An association-rulemining method is used to extract a sufficient number of important rules for the user's purpose rather than to extract all the rules meeting the criteria which are useful for misuse detection  ...  The proposed system includes fuzzy logic with a data mining method which is a class-association rule mining method based on genetic algorithm.  ...  from network audit data, and the support-confidence framework is utilized as a fitness function to judge the quality of each rule.  ... 
doi:10.5120/8489-2436 fatcat:x3ce5cu2jngrrbesdpi3hyggh4
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