Search Results - (( java implementation modified algorithm ) OR ( using sequences mining algorithm ))
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Separator Database and SPM Tree Framework for Mining Sequential Patterns Using Prefixspan with Pseudoprojection
Published 2008“…Future research includes exploring the use of separator Database in PrefixSpan with pseudoprojection to improve mining generalized sequential patterns, particularly in handling mining constrained sequential patterns.…”
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Separator Database and SPM Tree Framework for Mining Sequential Patterns Using Prefixspan with Pseudoprojection
Published 2008“…Future research includes exploring the use of separator Database in PrefixSpan with pseudoprojection to improve mining generalized sequential patterns, particularly in handling mining constrained sequential patterns.…”
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3
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. …”
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Sequential pattern mining using PrefixSpan with pseudoprojection and separator database
Published 2008“…Sequential pattern mining is a new branch of data mining science that solves inter-transaction pattern mining problems. …”
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Web Usage Mining Using GSP Algorithm: A Study on Sultanah Bahiyah Library Online Databases
Published 2008“…The goals of this study are to propose a suitable technique for preprocessing web log data of Sultanah Bahiyah Library online databases that can reduce the file size and to analyze the user's access pattern of the online databases using web usage mining. In this study web usage mining use sequential pattern technique with GSP algorithm. …”
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Data mining of protein sequences with amino acid position-based feature encoding technique
Published 2014“…In this paper, an amino acid position-based feature encoding technique is proposed to represent a protein sequence using a fixed length numeric feature vector. …”
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An Efficient Data Structure for General Tree-Like Framework in Mining Sequential Patterns Using MEMISP
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A comparative analysis of software engineering approaches for sequence analysis
Published 2013“…The proposal describes the concepts, tools, methodologies, and algorithms being used for sequence analysis. The sequences contain the precious information that needs to be mined for useful purposes. …”
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Analyzing DNA Sequences Using Clustering Algorithm
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OPTIMIZED MIN-MIN TASK SCHEDULING ALGORITHM FOR SCIENTIFIC WORKFLOWS IN A CLOUD ENVIRONMENT
Published 2023“…To achieve this, we propose a new noble mechanism called Optimized Min-Min (OMin-Min) algorithm, inspired by the Min-Min algorithm. The objectives of this work are: i) to provide a comprehensive review of the cloud and scheduling process; ii) to classify the scheduling strategies and scientific workflows; iii) to implement our proposed algorithm with various scheduling algorithms (i.e., Min-Min, Round-Robin, Max-Min, and Modified Max-Min) for performance comparison, within different cloudlet sizes (i.e., small, medium, large, and heavy) in three scientific workflows (i.e., Montage, Epigenomics, and SIPHT); and iv) to investigate the performance of the implemented algorithms by using CloudSim. …”
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Computational Discovery of Motifs Using Hierarchical Clustering Techniques
Published 2008“…Our algorithm is evaluated using two sets of DNA sequences with comparisons. …”
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Evaluation and optimization of frequent association rule based classification
Published 2014“…In this paper, a systematic way to evaluate the association rules discovered from frequent itemset mining algorithms, combining common data mining and statistical interestingness measures, and outline an appropriated sequence of usage is presented. …”
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Sequential pattern mining on library transaction data
Published 2010“…Application of data mining techniques in library data results interesting and useful patterns that can be used to improve services in university libraries. …”
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Sequential pattern mining using personalized minimum support threshold with minimum items
Published 2011“…The P_minsup is generated for each k-sequence by analyzing the overall support pattern distribution of the click stream data; while the min_i value gives the user the flexibility to gain control on the number of patterns to be generated on the next k-sequence by using the top min_i items. …”
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Prevention And Detection Mechanism For Security In Passive Rfid System
Published 2013“…The proposed protocol is designed with lightweight cryptographic algorithm, including XOR, Hamming distance, rotation and a modified linear congruential generator (MLCG). …”
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Effective mining on large databases for intrusion detection
Published 2014“…Results show that higher detection rate is achieved when using apriori algorithm on the proposed dataset. …”
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Automatic generation of content security policy to mitigate cross site scripting
Published 2016“…It can be extended to support generating CSP for contents that are modified by JavaScript after loading. Current approach inspects the static contents of URLs.…”
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Discovering decision algorithm of distance protective relay based on rough set theory and rule quality measure
Published 2011“…The discovered decision algorithm and association rule from the Rough-Set based data mining had been compared with and successfully validated by those discovered using the benchmarking Decision-Tree based data mining strategy. …”
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Evaluation and optimization of frequent, closed and maximal association rule based classification
Published 2014“…Real world applications of association rule mining have well-known problems of discovering a large number of rules, many of which are not interesting or useful for the application at hand.The algorithms for closed and maximal item sets mining significantly reduce the volume of rules discovered and complexity associated with the task, but the implications of their use and important differences with respect to the generalization power, precision and recall when used in the classification problem have not been examined.In this paper, we present a systematic evaluation of the association rules discovered from frequent, closed and maximal item set mining algorithms, combining common data mining and statistical interestingness measures, and outline an appropriate sequence of usage.The experiments are performed using a number of real-world datasets that represent diverse characteristics of data/items, and detailed evaluation of rule sets is provided as a whole and w.r.t individual classes. …”
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