Search Results - (( java application mining algorithm ) OR ( knowledge operation mining algorithm ))

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  1. 1
    Direct approach for mining association rules from structured XML data

    Direct approach for mining association rules from structured XML data by Abazeed, Ashraf Riad

    Published 2012
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  2. 2
    Separator Database and SPM Tree Framework for Mining Sequential Patterns Using Prefixspan with Pseudoprojection

    Separator Database and SPM Tree Framework for Mining Sequential Patterns Using Prefixspan with Pseudoprojection by Saputra , Dhany, Rambli, Dayang R.A., Foong, Oi Mean

    Published 2008
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  3. 3
    Knowledge discovery in distance relay event report: a comparative data-mining strategy of rough set theory with decision tree

    Knowledge discovery in distance relay event report: a comparative data-mining strategy of rough set theory with decision tree by Othman, Mohammad Lutfi, Aris, Ishak, Abdullah, Senan Mahmood, Ali, Md. Liakot, Othman, Mohammad Ridzal

    Published 2010
    “…This paper addresses these issues by intelligently divulging the knowledge hidden in the relay recorded event report using a data-mining strategy based on rough set theory and a rule-quality measure under supervised learning to discover the relay decision algorithm and association rule. …”
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  4. 4
    Discovering decision algorithm of distance protective relay based on rough set theory and rule quality measure

    Discovering decision algorithm of distance protective relay based on rough set theory and rule quality measure by Othman, Mohamad Lutfi

    Published 2011
    “…Thus, this thesis addresses these issues with the objective of intelligently divulging the knowledge hidden in the recorded event report at a relay device level using a data mining strategy based on Rough Set Theory, Genetic Algorithm and Rule Quality Measure under supervised learning within the framework of Knowledge Discovery in Database (KDD) in order to discover the relay’s decision algorithm (prediction rules) and, subsequently, the association rule. …”
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  5. 5
    Rough-Set-and-Genetic-Algorithm based data mining and Rule Quality Measure to hypothesize distance protective relay operation characteristics from relay event report

    Rough-Set-and-Genetic-Algorithm based data mining and Rule Quality Measure to hypothesize distance protective relay operation characteristics from relay event report by Othman, Mohammad Lutfi, Aris, Ishak, Othman, Mohammad Ridzal, Osman, Harussaleh

    Published 2011
    “…Firstly, the data mining approach of the integrated-Rough-Set-and-Genetic-Algorithm is used to discover the relay CD-decision algorithm. …”
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  6. 6
    Study and Implementation of Data Mining in Urban Gardening

    Study and Implementation of Data Mining in Urban Gardening by Mohana, Muniandy, Lee, Eu Vern

    Published 2019
    “…Attached sensors generate data and send these data to the Java Servlet application through a WIFI module. These data are processed and stored in appropriate formats in a MySQL server database. …”
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  7. 7
    Modeling and simulation of the industrial numerical distance relay aimed at knowledge discovery in resident event reporting

    Modeling and simulation of the industrial numerical distance relay aimed at knowledge discovery in resident event reporting by Othman, Mohammad Lutfi, Aris, Ishak, Abdul Wahab, Noor Izzri

    Published 2014
    “…In the motivation of tapping the strong potential of computational intelligence in discovering knowledge of protective relay operations using data mining, modeling and simulation of an actual industrial numerical distance relay and its recording facility are a vital requisite. …”
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  8. 8
    Twofold Integer Programming Model for Improving Rough Set Classification Accuracy in Data Mining.

    Twofold Integer Programming Model for Improving Rough Set Classification Accuracy in Data Mining. by Saeed, Walid

    Published 2005
    “…These tools are known as Data Mining (DM). One aims of DM is to discover decision rules for extracting meaningful knowledge. …”
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  9. 9
    Mining Sequential Patterns Using I-PrefixSpan

    Mining Sequential Patterns Using I-PrefixSpan by Dhany , Saputra, Rambli Dayang, R.A., Foong, Oi Mean

    Published 2007
    “…Sequential pattern mining is a relatively new data-mining problem with many areas of application. …”
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  10. 10
    A web-based implementation of k-means algorithms

    A web-based implementation of k-means algorithms by Lee, Quan

    Published 2022
    “…This stinginess of proximity measures in data mining tools is stifling the performance of the algorithm. …”
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  11. 11
    Mining Sequential Patterns using I-PrefixSpan

    Mining Sequential Patterns using I-PrefixSpan by Saputra , Dhany, Dayang R.A. Rambli, Foong, Oi Mean

    Published 2008
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    Citation Index Journal
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  12. 12
    An analysis of text mining factors enhancing the identification of relevant studies

    An analysis of text mining factors enhancing the identification of relevant studies by Khashfeh M., Mahmoud M.A., Ahmad M.S.

    Published 2023
    “…The second component is the search process that is operated by a pattern matching. The third process is the parsing that is operated by a text mining algorithm. …”
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  13. 13
    Novel rule base development from IED-resident big data for protective relay analysis expert system

    Novel rule base development from IED-resident big data for protective relay analysis expert system by Othman, Mohammad Lutfi, Aris, Ishak, Ananthapadmanabha, Thammaiah

    Published 2016
    “…This module is to provide the facility of intelligently maintaining the knowledge base of PRAY through the prior discovery of relay operations (association) rules from a novel integrated data mining approach of Rough-Set-Genetic-Algorithm-based rule discovery and Rule Quality Measure. …”
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  14. 14
    Data Mining On Machine Breakdowns And Effectiveness Of Scheduled Maintenance

    Data Mining On Machine Breakdowns And Effectiveness Of Scheduled Maintenance by Tan, Su Sze

    Published 2019
    “…This provides a large corpus of information retrievable for data mining and knowledge discovery. The case study is focused on the investigation of machine breakdown and the effectiveness of scheduled maintenance with the application of data mining. …”
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    Monograph
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  15. 15
    Features selection for intrusion detection system using hybridize PSO-SVM

    Features selection for intrusion detection system using hybridize PSO-SVM by Tabaan, Alaa Abdulrahman

    Published 2016
    “…The simulation will be carried on WEKA tool, which allows us to call some data mining methods under JAVA environment. The proposed model will be tested and evaluated on both NSL-KDD and KDD-CUP 99 using several performance metrics.…”
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  16. 16
    Adaptive firefly algorithm for hierarchical text clustering

    Adaptive firefly algorithm for hierarchical text clustering by Mohammed, Athraa Jasim

    Published 2016
    “…Text clustering is essentially used by search engines to increase the recall and precision in information retrieval. As search engine operates on Internet content that is constantly being updated, there is a need for a clustering algorithm that offers automatic grouping of items without prior knowledge on the collection. …”
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  17. 17
    Determining number of clusters using firefly algorithm with cluster merging for text clustering

    Determining number of clusters using firefly algorithm with cluster merging for text clustering by Mohammed, Athraa Jasim, Yusof, Yuhanis, Husni, Husniza

    Published 2015
    “…Such a scenario requires a dynamic text clustering method that operates without initial knowledge on a data collection.In this paper, a dynamic text clustering that utilizes Firefly algorithm is introduced.The proposed, aFAmerge, clustering algorithm automatically groups text documents into the appropriate number of clusters based on the behavior of firefly and cluster merging process. …”
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  18. 18
    Information extraction using Link Grammar

    Information extraction using Link Grammar by N., Zamin

    Published 2009
    “…LG appears within limited literature search to be the most suitable candidate algorithm. However, an exhaustive literature search will reveal the algorithm best suited to this application work. …”
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  19. 19
    K Nearest Neighbor Joins And Mapreduce Process Enforcement For The Cluster Of Data Sets In Bigdata

    K Nearest Neighbor Joins And Mapreduce Process Enforcement For The Cluster Of Data Sets In Bigdata by Md Shah, Wahidah, Othman, Mohd Fairuz Iskandar, Hussian Hassan, Ali Abdul, Talib, Mohammed Saad, Mohammed, Ali Abdul Jabbar

    Published 2018
    “…K Nearest Neighbor Joins (KNN join) are regarded as highly primitive and expensive operations in the data mining.The efficient use of KNN join has proven good results in finding the objects from two data sets prevailed in the huge databases.This has been achieved with the combination of K-Nearest Neighbor query and join operation to find the distinct objects from different data sets.MapReduce is a newly introduced program with the combination of Map Procedure method and Reduce Method widely used in BigData.MapReduce is enriched with parallel distributed algorithm to find the results on a cluster of data sets in BigData.In this paper,the combination of KNN join and MapReduce methods are utilized on the cluster of data sets in BigData for knowledge discovery.Exploring the pinpoint data from huge data sets stored in Big Data demands the distributed large scale data processing.The present research paper is focusing on generic steps for KNN joins exploration operations on MapReduce.The operations of KNN Join are targeted to perform the data partitioning and data pre-processing and necessary calculations.By utilizing the combination of KNN joins with MapReduce methods on BigData data sets will demonstrate a solution for complex computational analysis. …”
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  20. 20
    Computerized Maintenance Management System for Food Processing Industries

    Computerized Maintenance Management System for Food Processing Industries by M.A., Burhanuddin, A.R., Ahmad, M.I., Desa, M.Y., Zeratul

    Published 2007
    “…Breakdown define as total amount of time the equipment would normally be out of operation from the moment it fails until the moment it is fully repaired and operational. …”
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