Results 101 to 110 of about 10,877 (201)
Practical Approaches for Mining Frequent Patterns in Molecular Datasets
Bioinformatics and Biology Insights, 2016 Pattern detection is an inherent task in the analysis and interpretation of complex and continuously accumulating biological data. Numerous itemset mining algorithms have been developed in the last decade to efficiently detect specific pattern classes in
Stefan Naulaerts +6 more
doaj +1 more source
A Framework for High-Accuracy Privacy-Preserving Mining
, 2004 To preserve client privacy in the data mining process, a variety of techniques based on random perturbation of data records have been proposed recently.
Agrawal, Shipra, Haritsa, Jayant R.
core +3 more sources
Association rules recommendation algorithm supporting recommendation nonempty
Tongxin xuebao, 2017 Existing association rule recommendation technologies were focus on extraction efficiency of association rule in data mining.However,it lacked consideration of recommendation balance between popular and unusual data and efficient processing.In order to ...
Ming HE, Wei-shi LIU, Jiang ZHANG
doaj +2 more sources
A NOVEL ALGORITHM FOR ASSOCIATION RULE MINING FROM DATA WITH INCOMPLETE AND MISSING VALUES [PDF]
ICTACT Journal on Soft Computing, 2011 Missing values and incomplete data are a natural phenomenon in real datasets. If the association rules mine incomplete disregard of missing values, mistaken rules are derived.
K. Rameshkumar
doaj
Engineering ProceedingsHigh-utility itemset mining (HUIM) utilizes the threshold value to extract HUI from the transactional database. However, it is difficult to define an optimal threshold value, since it depends on the domain knowledge of the application.
Ye-In Chang +4 more
doaj +1 more source
Jurnal Informatika, 2007 Taking attendance from employees always becomes a problem for Human Resource Department (HRD) in many companies lately. Although there is an automatic check-lock machine, it still has a weakness.
Gregorius Satia Budhi +1 more
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FREQUENT ITEMSETS MINING FOR BIG DATA
, 2019 Frequent Itemsets Mining (FIM) is a fundamental mining model and plays an important role in Data Mining. It has a vast range of application fields and can be employed as a key calculation phase in many other mining models such as Association Rules, Correlations, Classifications, etc. Generally speaking, FIM counts the frequencies of co-occurrence items,
openaire +2 more sources
A primer to frequent itemset mining for bioinformatics. [PDF]
Brief Bioinform, 2015 Naulaerts S +6 more
europepmc +1 more source
CisMiner: genome-wide in-silico cis-regulatory module prediction by fuzzy itemset mining. [PDF]
PLoS One, 2014 Navarro C +4 more
europepmc +1 more source
An effectiveness assessment ensemble for transmission corridor mechanized construction schemes based on weighted itemset mining and factor criticality analysis. [PDF]
Sci RepYang X +5 more
europepmc +1 more source