Search Results - (( deviation detection method algorithm ) OR ( problem implementation mining algorithm ))
Search alternatives:
- problem implementation »
- implementation mining »
- deviation detection »
- method algorithm »
- mining algorithm »
-
1
Deviation detection in text using conceptual graph interchange format and error tolerance dissimilarity function
Published 2012“…We propose a novel error tolerance dissimilarity algorithm to detect deviations in the CGIFs. We evaluate our method in the context of analyzing real world financial statements for identifying deviating performance indicators. …”
Get full text
Get full text
Get full text
Article -
2
Direct approach for mining association rules from structured XML data
Published 2012“…The thesis also provides a two different implementation of the modified FLEX algorithm using a java based parsers and XQuery implementation. …”
Get full text
Get full text
Thesis -
3
A Rough-Apriori Technique in Mining Linguistic Association Rules
Published 2008“…It uses the rough membership function to capture the linguistic interval before implementing the Apriori algorithm to mine interesting association rules. …”
Get full text
Get full text
Get full text
Book Chapter -
4
ANALYSIS OF CUSTOMER SERVICE BUSINESS PROCESS USING DATA MINING
Published 2020“…Hence, this paper contribute to justify by the basic concepts of data mining, described the selected types and models of algorithms, and the process of data mining by using R Tools.…”
Get full text
Get full text
Final Year Project -
5
Fault diagnostic algorithm for precut fractionation column
Published 2004“…Hazard and Operability Study (HAZOP) is used to support the diagnosis task. The algorithm has been successful in detecting the deviations of each variable by testing the data set. …”
Get full text
Get full text
Conference or Workshop Item -
6
Comparative study of apriori-variant algorithms
Published 2016“…One of data mining methods is frequent itemset mining that has been implemented in real world applications, such as identifying buying patterns in grocery and online customers’ behavior.Apriori is a classical algorithm in frequent itemset mining, that able to discover large number or itemset with a certain threshold value. …”
Get full text
Get full text
Get full text
Conference or Workshop Item -
7
Algorithm enhancement for host-based intrusion detection system using discriminant analysis
Published 2004“…Anomaly detection algorithms model normal behavior. Anomaly detection models compare sensor data to normal patterns learned from the training data by using statistical method and try to detect activity that deviates from normal activity. …”
Get full text
Get full text
Thesis -
8
-
9
Scalable approach for mining association rules from structured XML data
Published 2009“…Many techniques have been proposed to tackle the problem of mining XML data we study the various techniques to mine XML data and yet We presented a java based implementation of FLEX algorithm for mining XML data.…”
Get full text
Get full text
Conference or Workshop Item -
10
A study on advanced statistical analysis for network anomaly detection
Published 2005“…Anomaly detection algorithms model normal behavior. Anomaly detection models compare sensor data to normal patterns learned from the training data by using statistical method and try to detect activity that deviates from normal activity. …”
Get full text
Monograph -
11
Mining association rules from structured XML data
Published 2009“…Many techniques have been proposed to tackle the problem of mining XML data. We study the various techniques to mine XML data and yet We presented a java based implementation of FLEX algorithm for mining XML data.…”
Get full text
Get full text
Conference or Workshop Item -
12
Analysis of Data Mining Tools for Android Malware Detection
Published 2019“…However, the problem arises in deciding the most appropriate machine learning techniques or algorithm on particular tools to be implemented on particular data. …”
Get full text
Get full text
Get full text
Article -
13
Parameter estimation and outlier detection in linear functional relationship model / Adilah Abdul Ghapor
Published 2017“…The simulation results indicate that the proposed method is suitable to detect a single outlier. As for the multiple outliers, a clustering algorithm is considered and a dendogram to visualise the clustering algorithm is used. …”
Get full text
Get full text
Get full text
Thesis -
14
A novel approach to data mining using simplified swarm optimization
Published 2011“…Therefore, the proposed SSO rule-based classifier with local search strategies has offered a new paradigm shift in solving complex problems in data mining which may not be able to be solved by other benchmark classifiers.…”
Get full text
Get full text
Thesis -
15
Development of a rule-based fault diagnostic advisory system for precut fractionation column
Published 2005“…The advisory system algorithm used process history based method and presented by rule-based approach. …”
Get full text
Get full text
Thesis -
16
Comparative study of clustering-based outliers detection methods in circular-circular regression model
Published 2021“…This paper is a comparative study of several algorithms for detecting multiple outliers in circular-circular regression model based on the clustering algorithms. …”
Get full text
Get full text
Get full text
Article -
17
Attribute related methods for improvement of ID3 Algorithm in classification of data: A review
Published 2020“…Decision tree is an important method in data mining to solve the classification problems. There are several learning algorithms to implement the decision tree but the most commonly-used is ID3 algorithm. …”
Get full text
Get full text
Get full text
Article -
18
Comparative study of clustering-based outliers detection methods in circular-circular regression model
Published 2021“…This paper is a comparative study of several algorithms for detecting multiple outliers in circular-circular regression model based on the clustering algorithms. …”
Get full text
Get full text
Get full text
Article -
19
Comparative study of clustering-based outliers detection methods in circularcircular regression model
Published 2021“…This paper is a comparative study of several algorithms for detecting multiple outliers in circular-circular regression model based on the clustering algorithms. …”
Get full text
Get full text
Get full text
Article -
20
An enhanced intelligent database engine by neural network and data mining
Published 2000“…An Intelligent Database Engine (IDE) is developed to solve any classification problem by providing two integrated features: decision-making by a backpropagation (BP) neural network (NN) and decision support by Apriori, a data mining (DM) algorithm. …”
Get full text
Get full text
Article
