Search Results - (( pattern mining algorithm ) OR ((( patterns graph algorithm ) OR ( patterns colony algorithm ))))

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  1. 1
    Web user navigation pattern mining approach based on graph partitioning algorithm.

    Web user navigation pattern mining approach based on graph partitioning algorithm. by Jalali, Mehrdad, Mustapha, Norwati, Mamat, Ali, Sulaiman, Md. Nasir

    Published 2008
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  2. 2
    A Web-Based Recommendation System To Predict User Movements Through Web Usage Mining

    A Web-Based Recommendation System To Predict User Movements Through Web Usage Mining by Jalali, Mehrdad

    Published 2009
    “…The approach in the offline phase is based on the new graph partitioning algorithm to model user navigation patterns for the navigation patterns mining. …”
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  3. 3
    WebPUM : a web-based recommendation system to predict user future movements.

    WebPUM : a web-based recommendation system to predict user future movements. by Jalali, Mehrdad, Mustapha, Norwati, Sulaiman, Md. Nasir, Mamat, Ali

    Published 2010
    “…The approach is based on the new graph partitioning algorithm to model user navigation patterns for the navigation patterns mining phase. …”
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  4. 4
    Data normalization techniques in swarm-based forecasting models for energy commodity spot price

    Data normalization techniques in swarm-based forecasting models for energy commodity spot price by Yusof, Yuhanis, Mustaffa, Zuriani, Kamaruddin, Siti Sakira

    Published 2014
    “…Data mining is a fundamental technique in identifying patterns from large data sets.The extracted facts and patterns contribute in various domains such as marketing, forecasting, and medical.Prior to that, data are consolidated so that the resulting mining process may be more efficient.This study investigates the effect of different data normalization techniques.which are Min-max, Z-score and decimal scaling, on Swarm-based forecasting models.Recent swarm intelligence algorithms employed includes the Grey Wolf Optimizer (GWO) and Artificial Bee Colony (ABC).Forecasting models are later developed to predict the daily spot price of crude oil and gasoline.Results showed that GWO works better with Z-score normalization technique while ABC produces better accuracy with the Min-Max.Nevertheless, the GWO is more superior than ABC as its model generates the highest accuracy for both crude oil and gasoline price.Such a result indicates that GWO is a promising competitor in the family of swarm intelligence algorithms.…”
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  5. 5
    Predicting stroke using ant colony optimization algorithm / Azfaruddin Azri and Rizauddin Saian

    Predicting stroke using ant colony optimization algorithm / Azfaruddin Azri and Rizauddin Saian by Azri, Azfaruddin, Saian, Rizauddin

    Published 2023
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  6. 6
    An improved ACS algorithm for data clustering

    An improved ACS algorithm for data clustering by Mohammed Jabbar, Ayad, Ku-Mahamud, Ku Ruhana, Sagban, Rafid

    Published 2020
    “…Data clustering is a data mining technique that discovers hidden patterns by creating groups (clusters) of objects. …”
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  7. 7
    Lexicon-based and immune system based learning methods in Twitter sentiment analysis

    Lexicon-based and immune system based learning methods in Twitter sentiment analysis by Jantan, Hamidah, Drahman, Fatimatul Zahrah, Alhadi, Nazirah, Mamat, Fatimah

    Published 2016
    “…In future work, the accuracy of proposed model can be strengthened by comparative study with other heuristic based searching algorithms such as genetic algorithm, ant colony optimization, swam algorithms and etc.…”
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  8. 8
    Deviation detection in text using conceptual graph interchange format and error tolerance dissimilarity function

    Deviation detection in text using conceptual graph interchange format and error tolerance dissimilarity function by Kamaruddin, Siti Sakira, Hamdan, Abdul Razak, Abu Bakar, Azuraliza, Mat Nor, Fauzias

    Published 2012
    “…This paper focuses on a graph-based approach for text representation and presents a novel error tolerance dissimilarity algorithm for deviation detection. …”
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  9. 9
    Enhancement of text representation for Indonesian document summarization with deep sequential pattern mining

    Enhancement of text representation for Indonesian document summarization with deep sequential pattern mining by Dian Sa’adillah Maylawati

    Published 2023
    “…First, this study combines SPM with Sentence Scoring method as feature-based approach and Bellman-Ford algorithm as graph-based to validate the performance of SPM. …”
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  10. 10
    Modifying iEclat algorithm for infrequent patterns mining

    Modifying iEclat algorithm for infrequent patterns mining by Julaily Aida, J., Mustafa, M.

    Published 2018
    “…This paper proposes an enhancement algorithm based on iEclat algorithms for mining infrequent pattern.…”
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  11. 11
    Modifying iEclat algo ithm for infrequent patterns mining

    Modifying iEclat algo ithm for infrequent patterns mining by Julaily Aida, Jusoh, Mustafa, Man

    Published 2018
    “…This paper proposes an enhancement algorithm based on iEclat algorithms for mining infrequent pattern.…”
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  12. 12
    Performance of IF-Postdiffset and R-Eclat Variants in Large Dataset

    Performance of IF-Postdiffset and R-Eclat Variants in Large Dataset by Julaily Aida, Jusoh, Wan Aezwani, Wan Abu Bakar, Mustafa, Man

    Published 2018
    “…The multiple variants in the R-Eclat algorithm generate varied performances in infrequent mining patterns. …”
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  13. 13
    Efficient prime-based method for interactive mining of frequent patterns.

    Efficient prime-based method for interactive mining of frequent patterns. by Mohammad Hossein, Nadimi Shahraki, Mustapha, Norwati, Sulaiman, Md. Nasir, Mamat, Ali

    Published 2011
    “…Since rerunning mining algorithms from scratch is very costly and time-consuming, researchers have introduced interactive mining of frequent patterns. …”
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  14. 14
    Collective interaction filtering with graph-based descriptors for crowd behaviour analysis

    Collective interaction filtering with graph-based descriptors for crowd behaviour analysis by Wong, Pei Voon

    Published 2018
    “…At the high-level, the result of Collective Interaction Filtering is used in group motion pattern mining to predict collectiveness, uniformity, stability, and conflict generic descriptors. …”
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  15. 15
    Prime-based method for interactive mining of frequent patterns

    Prime-based method for interactive mining of frequent patterns by Nadimi-Shahraki, Mohammad-Hossein

    Published 2010
    “…Since rerunning the mining algorithms from scratch can be very time consuming, researchers have introduced interactive mining to find proper patterns by using the current mining model with various minsup. …”
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  16. 16
    DFP-growth: An efficient algorithm for mining frequent patterns in dynamic database

    DFP-growth: An efficient algorithm for mining frequent patterns in dynamic database by Zailani, Abdullah, Herawan, Tutut, Noraziah, Ahmad, Mustafa, Mat Deris

    Published 2012
    “…Nowadays, FP-Growth is one of the famous and benchmarked algorithms to mine the frequent patterns from FP-Tree data structure. …”
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  17. 17
    Algorithms for frequent itemset mining: a literature review

    Algorithms for frequent itemset mining: a literature review by Chee, C.-H., Jaafar, J., Aziz, I.A., Hasan, M.H., Yeoh, W.

    Published 2018
    “…This paper reviews and presents a comparison of different algorithms for Frequent Pattern Mining (FPM) so that a more efficient FPM algorithm can be developed. …”
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  18. 18
    Frequent Lexicographic Algorithm for Mining Association Rules

    Frequent Lexicographic Algorithm for Mining Association Rules by Mustapha, Norwati

    Published 2005
    “…The mined frequent patterns are then used in generating association rules. …”
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  19. 19
    A numerical method for frequent pattern mining

    A numerical method for frequent pattern mining by Mustapha, Norwati, Nadimi-Shahraki, Mohammad-Hossein, Mamat, Ali, Sulaiman, Md. Nasir

    Published 2009
    “…Frequent pattern mining is one of the active research themes in data mining. …”
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  20. 20
    A frequent pattern mining algorithm based on FP-growth without generating tree

    A frequent pattern mining algorithm based on FP-growth without generating tree by Tohidi, Hossein, Ibrahim, Hamidah

    Published 2010
    “…An interesting method to frequent pattern mining without generating candidate pattern is called frequent-pattern growth, or simply FP-growth, which adopts a divide-and-conquer strategy as follows. …”
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