Results 71 to 80 of about 801,363 (206)

arules - A Computational Environment for Mining Association Rules and Frequent Item Sets [PDF]

Mining frequent itemsets and association rules is a popular and well researched approach for discovering interesting relationships between variables in large databases.
Bettina Grün, Kurt Hornik, Michael Hahsler   +2 more
core  

Towards efficiently mining closed high utility itemsets from incremental databases [PDF]

, 2018
The set of closed high-utility itemsets (CHUIs) concisely represents the exact utility of all itemsets. Yet, it can be several orders of magnitude smaller than the set of all high-utility itemsets.
Ramampiaro, Heri, Dam, Thu-Lan, Nørvåg, Kjetil, Duong, Quang-Huy   +3 more
core   +2 more sources

AN ADABOOST OPTIMIZED CCFIS BASED CLASSIFICATION MODEL FOR BREAST CANCER DETECTION [PDF]

Journal of Engineering Science and Technology, 2017
Classification is a Data Mining technique used for building a prototype of the data behaviour, using which an unseen data can be classified into one of the defined classes.
CHANDRASEKAR RAVI, NEELU KHARE
doaj  

A multi‐agent K‐means with case‐based reasoning for an automated quality assessment of software requirement specification

IET Communications, Volume 19, Issue 1, January/December 2025.
This paper proposed an Automated Quality Assessment of SRS (AQA‐SRS) framework by integrating four popular methods which are; NLP, K‐means, MAS, and CBR to assess the quality of SRS documents. The NLP utilize for feature extraction, K‐means for features clustering, MAS for interactive assessment and feature selection decision, and CBR for managing the ...
Mohammed Ahmed Jubair, Salama A. Mostafa, Aida Mustapha, Mohamad Aizi Salamat, Mustafa Hamid Hassan, Mazin Abed Mohammed, Fahad Taha AL‐Dhief   +6 more
wiley   +1 more source

H.: Closed non-derivable itemsets

, 2006
. Itemset mining typically results in large amounts of redundant itemsets. Several approaches such as closed itemsets, non-derivable itemsets and generators have been suggested for losslessly reducing the amount of itemsets.
Hannu Toivonen, Juho Muhonen
core  

Efficient Incremental Mining of Top-K Frequent Closed Itemsets

, 2007
In this work we study the mining of top-$K$ frequent closed itemsets, a recently proposed variant of the classical problem of mining frequent closed itemsets where the support threshold is chosen as the maximum value sufficient to guarantee that the ...
PIETRACAPRINA, ANDREA ALBERTO, VANDIN, FABIO   +1 more
core   +1 more source

Perbaikan Algoritma Charm Untuk Penggalian Frequent Closed Itemsets [PDF]

, 2007
Penggalian frequent closed itemsets merupakan salah satu bagian penting dari penggalian kaidah asosiasi (association rule) karena dapat secara unik menentukan himpunan semua frequent itemsets dan supportnya.
Mardiyanto, Mardiyanto
core  

DisClose: Discovering colossal closed itemsets via a memory efficient compact row-tree

, 2013
A recent focus in itemset mining has been the discovery of frequent itemsets from high-dimensional datasets. With exponentially increasing running time as average row length increases, mining such datasets renders most conventional algorithms impractical.
Keane, John A, Nurul F. Zulkurnain, David J. Haglin, John A. Keane, Zulkurnain , N.F., Haglin, David J.   +5 more
core   +1 more source

Application of data mining based on association rules in teaching evaluation systems: A comparative multi-algorithm study

Array
The rapid expansion of digital teaching-evaluation systems has created opportunities to improve educational decision-making through interpretable data-mining techniques.
Xiaoyan Zhu
doaj   +1 more source

Catch the Moment: Maintaining Closed Frequent Itemsets

, 2008
This paper considers the problem of mining closed frequent itemsets over a data stream sliding window using limited memory space. We design a synopsis data structure to monitor transactions in the sliding window so that we can output the current closed
Philip S. Yu, Over Data Stream, Yun Chi, Richard R. Muntz, Haixun Wang   +4 more
core