Clustering and association rule mining-based traffic analysis and prediction of Dhaka

Ahmed, Muyeed; Imtiaz, Mir Tahsin; Khan, Raiyan; Rahman, Rashedur M.

doi:10.1504/ijkedm.2018.095524

Cited by 3 publications

(3 citation statements)

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“…Clustering is an unsupervised approach for grouping similar documents (Siddiky et al, 2012;Jayabharathy and Kanmani, 2015). The goal of most clustering algorithms is to minimize the objective function (J) that measures the quality of clusters to find the optimum J which is the sum of the squared distances between each cluster center and each data point (Ahmed et al, 2018). There are two major clustering approaches: hard and fuzzy (soft).…”

Section: Methodsmentioning

confidence: 99%

Application of Fuzzy Clustering for Text Data Dimensionality Reduction

Karami

2019

IJKEDM

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Large textual corpora are often represented by the document-term frequency matrix whose elements are the frequency of terms; however, this matrix has two problems: sparsity and high dimensionality. Four dimension reduction strategies are used to address these problems. Of the four strategies, unsupervised feature transformation (UFT) is a popular and efficient strategy to map the terms to a new basis in the document-term frequency matrix. Although several UFTbased methods have been developed, fuzzy clustering has not been considered for dimensionality reduction. This research explores fuzzy clustering as a new UFT-based approach to create a lower-dimensional representation of documents. Performance of fuzzy clustering with and without using global term weighting methods is shown to exceed principal component analysis and singular value decomposition. This study also explores the effect of applying different fuzzifier values on fuzzy clustering for dimensionality reduction purpose.

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Section: Methodsmentioning

confidence: 99%

Application of Fuzzy Clustering for Text Data Dimensionality Reduction

Karami

2019

IJKEDM

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“…Muyeed Ahmed, Mir Tahsin Imtiaz, Raiyan Khan and Rashedur M. Rahman [4] Traffic is one of the major problems for any populated city. Currently, there are many traffic alert systems available and almost all of them work with user submitted inputs to give those alerts.…”

Section: Literature Survey On Association Rule Miningmentioning

confidence: 99%

“…From the analysis of abstracted patterns, decision-making process can be done very easily. Many modern intrusion detection systems are based on data mining and database-centric architecture [4], where a number of data mining techniques have been found. Data mining-based intrusion detection systems can be classified into misuse detection and anomaly detection.…”

Section: Introductionmentioning

confidence: 99%

Association Rule Mining for Intrusion Detection System: A Survey

Selvamani¹,

Selvi²

2019

AJEAT

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Many modern intrusion detection systems are based on data mining and database-centric architecture, where a number of data mining techniques have been found. Among the most popular techniques, association rule mining is one of the important topics in data mining research. This approach determines interesting relationships between large sets of data items. This technique was initially applied to the so-called market basket analysis, which aims at finding regularities in shopping behaviour of customers of supermarkets. In contrast to dataset for market basket analysis, which takes usually hundreds of attributes, network audit databases face tens of attributes. So the typical Apriori algorithm of association rule mining, which needs so many database scans, can be improved, dealing with such characteristics of transaction database. In this paper, a literature survey on the Association Rule Mining has carried out.

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Analysis of Association Rules of Investment Risk and Accounting Based on Artificial Intelligence Model

Chen¹

2020

Lecture Notes in Electrical Engineering

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Clustering and association rule mining-based traffic analysis and prediction of Dhaka

Cited by 3 publications

References 0 publications

Application of Fuzzy Clustering for Text Data Dimensionality Reduction

Application of Fuzzy Clustering for Text Data Dimensionality Reduction

Association Rule Mining for Intrusion Detection System: A Survey

Analysis of Association Rules of Investment Risk and Accounting Based on Artificial Intelligence Model

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