Results 111 to 120 of about 45,837 (241)

IIS-Mine: A new efficient method for mining frequent itemsets [PDF]

Maejo International Journal of Science and Technology, 2012
A new approach to mine all frequent itemsets from a transaction database isproposed. The main features of this paper are as follows: (1) the proposed algorithmperforms database scanning only once to construct a data structure called an invertedindex ...
Supatra Sahaphong
doaj  

Mining Assocation Rules Using Frequent Closed Itemsets

, 2005
In the domain of knowledge discovery in databases and its computational part called data mining, many works addressed the problem of association rule extraction that aims at discovering relationships between sets of items (binary attributes). An example association rule fitting in the context of market basket data analysis is cereal Ù milk ® sugar ...
openaire   +2 more sources

On Maximal Frequent Itemsets Mining with Constraints

International Conference on Principles and Practice of Constraint Programming, 2018
Saïd Jabbour, Fatima Ezzahra Mana, Imen Ouled Dlala, Badran Raddaoui, L. Sais   +4 more
semanticscholar   +1 more source

Frequent itemset mining on multiprocessor systems

, 2014
Frequent itemset mining is an important building block in many data mining applications like market basket analysis, recommendation, web-mining, fraud detection, and gene expression analysis. In many of them, the datasets being mined can easily grow up to hundreds of gigabytes or even terabytes of data.
openaire   +2 more sources

Application of frequent itemsets mining to analyze patterns of one-stop visits in Taiwan. [PDF]

PLoS One, 2011
Tu CY, Chen TJ, Chou LF.
europepmc   +1 more source

Mining personalized core traditional Chinese medicine prescriptions for rheumatoid arthritis and elucidating their mechanisms via frequent closed Itemset compression and multilevel network pharmacology. [PDF]

Front Mol Biosci
Chen X, Yu J, Dong X, Chen Z, Tian J, Zhao M, Jiang M, Guo H, Zhou X, Fa L, Li Y, Zhang L.   +11 more
europepmc   +1 more source

Application of improved FP-tree algorithm in rural accurate information service. [PDF]

Sci Rep
Jin Y, Zhao J, Li X, Wu J.
europepmc   +1 more source

Exploration of association rule mining between lost-linking features and modes of loan customers using the FP-growth algorithm for risk warning strategies. [PDF]

PLoS One
Wang J, Jiang X, He Y, Guan B, Deng C.
europepmc   +1 more source

Multi-level screening method for network security alarms based on DBSCAN algorithm and rete rule inference. [PDF]

Sci Rep
Ni L, Zhang S, Huang K, Wang Y.
europepmc   +1 more source

A high utility itemsets mining algorithm based on co-evolution. [PDF]

Sci Rep
Yang W, Han M, Dai Z, Li J, Ding J.
europepmc   +1 more source