Please wait ...
0% Complete
Home
/
14th International Conference on Computer and Knowledge Engineering
An Improved and Accurate Measure for Mining Correlated High-utility Itemsets
Authors :
Amir Masoud Heidari Orojloo
1
Morteza Keshtkaran
2
1- School of electrical and computer engineering University of Shiraz Shiraz, Iran
2- School of electrical and computer engineering University of Shiraz Shiraz, Iran
Keywords :
high-utility itemset mining،correlated high-utility itemset mining،correlation measure،Kulczynski measure،imbalanced ratio
Abstract :
This paper introduces an improved version of the Kulczynski measure, a widely used measure for mining correlated high-utility itemsets. This improved measure aims to achieve high accuracy while efficiently extracting itemsets with high utility that are also correlated. Using the Kulczynski measure often results in the generation of imbalanced itemsets in the mining process. In this paper, by considering the imbalance ratio measure in conjunction with the Kulczynski measure, the number of imbalanced itemsets is reduced significantly. To evaluate the performance of the improved measure, the effect of using this measure in comparison with the Kulczynski measure on the standard datasets is considered in the experiments. The results demonstrate the superior accuracy and advantage of using this correlation measure compared to its competitor.
Papers List
List of archived papers
Automating Theory of Mind Assessment with a LLaMA-3-Powered Chatbot: Enhancing Faux Pas Detection in Autism
Avisa Fallah - Ali Keramati - Mohammad Ali Nazari - Fatemeh Sadat Mirfazeli
Attentional Bi-LSTM for Multivariate Time Series Forecasting on Edge Devices: A Case Study on NanoPi Neo Plus2
Navid Hajizadeh - Saeed Yazdani - Sara Ershadi-Nasab
A Comparative Analysis of Clinical Note Categories for Mortality Prediction in ICU Patients
Maryam Karrabi - Mohsen Kahani - Mina Afzali - Nadieh Armin
Multi-Digit Handwritten Recognition: A CNN-LSTM Hybrid Approach with Wavelet Transforms
Amin Kazempour - Jafar Tanha
Automatic Detection and Risk Assessment of Session Management Vulnerabilities in Web Applications
Nasrin Garmabi - Mohammad Ali Hadavi
Swin-RSCBNet: A Transformer-Based Network for Skin Cancer Segmentation with Multi-Scale and Attention Modules
Benyamin Mirab Golkhatmi - Mostafa Heydari - Mahboobeh Houshmand - Seyyed Abed Hosseini
An effective hybrid algorithm for locating splicing forgery image
Seyed Hesamoddin Hosseini - Amene Vatanparast - Amir Hossein Taherinia
Adaptive Multi-Scale Attentional Network for Semantic Segmentation of Remote Sensing Images
Melika Zare - Sattar Hashemi
Hate Sentiment Recognition System For Persian Language
Pegah Shams jey - Arash Hemmati - Ramin Toosi - Mohammad ali Akhaee
Non-Negative Matrix Factorization improves Residual Neural Networks
Hojjat Moayed
more
Samin Hamayesh - Version 44.8.0