Search Results - (( processes interaction mining algorithm ) OR ( java application stemming algorithm ))

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  1. 1

    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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    Article
  2. 2

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

    Published 2010
    “…At first, a general architecture for interactive mining is proposed consisting of two isolated components: mining model and mining process. …”
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    Thesis
  3. 3

    Analysis using data mining techniques: the exploration and review data of diabetes patients / Syarifah Adilah Mohamed Yusoff ... [et al.] by Mohamed Yusoff, Syarifah Adilah, Othman, Jamal, Johan, Elly Johana, Mohd Mydin, Azlina, Wan Mohamad, Wan Anisha

    Published 2025
    “…In this statistical summary procedure, the distribution of attributes and their interactions are crucial for accurately processing the data in accordance with the selected classification or data mining techniques to be performed. …”
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    Article
  4. 4

    Comparative study of machine learning algorithms in data classification by Tan, Kai Jun

    Published 2025
    “…In many different fields, data mining, the process of identifying significant patterns in historical data, is essential to decision-making. …”
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    Final Year Project / Dissertation / Thesis
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    A norms mining approach to norms detection in multi-agent systems by A. Mahmoud, Moamin, Ahmad, Mohd Sharifuddin, Ahmad, Azhana, Mohd Yusoff , Mohd Zaliman, Mustapha, Aida

    Published 2012
    “…In this technique, the visitor agent is equipped with an algorithm, which detects the potential norms through the system's log file, interactions with the local agents, and observing the local agents in action. …”
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    Conference or Workshop Item
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    Social media mining: a genetic based multiobjective clustering approach to topic modelling by Rayner Alfred, Loo Yew Jie, Joe Henry Obit, Yuto Lim, Haviluddin Haviluddin, Azreen Azman

    Published 2021
    “…Social media mining is the process of collecting large datasets from user-generated content and extracting and analyzing social media interactions to recognize meaningful patterns in individual and social behavior. …”
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    Article
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    Social media mining: a genetic based multiobjective clustering approach to topic modelling by Alfred, Rayner, Loo, Yew Jie, Obit, Joe Henry, Lim, Yuto, Haviluddin, Haviluddin, Azman, Azreen

    Published 2021
    “…Social media mining is the process of collecting large datasets from user-generated content and extracting and analyzing social media interactions to recognize meaningful patterns in individual and social behavior. …”
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    Article
  9. 9

    A norms mining approach to norms detection in multi-agent systems by Mahmoud M.A., Ahmad M.S., Ahmad A., Mohd Yusoff M.Z., Mustapha A.

    Published 2023
    “…In this technique, the visitor agent is equipped with an algorithm, which detects the potential norms through the system's log file, interactions with the local agents, and observing the local agents in action. …”
    Conference paper
  10. 10

    Learner’s emotion prediction using production rules classification algorithm through brain computer interface tool by Nurshafiqa Saffah, Mohd Sharif

    Published 2018
    “…Classification and prediction are the functions provided by the data mining techniques that suit in EEG signal processing. …”
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    Thesis
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    Improved building roof type classification using correlation-based feature selection and gain ratio algorithms by Norman, M., Mohd Shafri, Helmi Zulhaidi, Pradhan, Biswajeet, Yusuf, B.

    Published 2017
    “…Accurate feature selection is a necessary step to improve the accuracy of classification. This process depends on the number of feature attributes available for interactive synthesis of common characteristics that discriminate different features. …”
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    Conference or Workshop Item
  12. 12

    Clustering of large time-series datasets using a multi-step approach / Saeed Reza Aghabozorgi Sahaf Yazdi by Yazdi, Saeed Reza Aghabozorgi Sahaf

    Published 2013
    “…Time-series clustering is not only useful as an exploratory technique but also as a subroutine in more complex data mining algorithms. As a result, time-series clustering (as a part of temporal data mining research) has attracted increasing interest for use in various areas such as medicine, biology, finance, economics, and in the Web. …”
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    Thesis
  13. 13

    Framework for stream clustering of trajectories based on temporal micro clustering technique by Abdulrazzaq, Musaab Riyadh

    Published 2018
    “…The algorithm assigns a life time for each newly created temporal micro clusters so that the new incoming batch of trajectories segments will interact only with the non-expired temporal micro clusters. …”
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    Thesis
  14. 14

    Extracting Tweets Using R in The Context of Ethical Issues by Mohamed Najid, Mohamad Hafizuddin, Zulkifli, Zahidah, Othman, Roslina, Rokis, Rohaiza

    Published 2021
    “…As a result of the data extraction, 1075 public tweets were collected through the search API. The simple algorithm is capable to facilitating the process of extracting data from Twitter, such that it easily known to the public tweets that exist in a given time period and this can be used as reference material for further development process. …”
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    Proceeding Paper
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    Web page design for electronic commerce / Lee Fong Wai by Lee , Fong Wai

    Published 2003
    “…Also includes a brief explanation about the interaction of this subsystem with the Online Shopping Submission and Processing Subsystem, which is developed by my teammate. …”
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    Thesis
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    Ranking-based pruning and weighted support model for gene association in frequent itemsets / Sofianita Mutalib by Mutalib, Sofianita

    Published 2019
    “…High dimensional dataset presented by SNPs confirmed the reason to apply row enumeration strategy algorithm to mine frequent closed itemsets. It is found that SNPs with known risks to Type 2 Diabetes Mellitus (T2DM) occur in low support values, that cause the process of searching frequent itemsets to be repeated many times until the low support values are retrieved. …”
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    Thesis
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