Search Results - (( java implementation modified algorithm ) OR ( using task clustering algorithm ))

Refine Results
  1. 1

    An ensemble data summarization approach based on feature transformation to learning relational data by Chung, Seng Kheau

    Published 2015
    “…A genetic algorithm (GA) is also used to find the best centroids for all the clusters generated cluster centroids. …”
    Get full text
    Get full text
    Get full text
    Thesis
  2. 2

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

    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. 3

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

    Published 2018
    “…On the other hand, the offline phase is evoked when the user requests to view the overall clustering results. The DBSCAN algorithm is used to perform the macro clustering task by replacing the distance between trajectories segments with the distance between the temporal micro-clusters. …”
    Get full text
    Get full text
    Thesis
  4. 4

    An intelligent categorization tool for malay research articles by Mohd Norhisham Razali, Rayner Alfred, Chin, Kim On

    Published 2015
    “…Hence, by increasing the mapping percentage for the bilingual clusters, a more robust clustering algorithm can be developed for clustering bilingual documents. …”
    Get full text
    Get full text
    Research Report
  5. 5
  6. 6
  7. 7

    A clustering technique using single pass clustering algorithm for search engine by Indra, Z., Zamin, N., Jaafar, J.

    Published 2014
    “…In this research, a clustering technique for search engine using Single Pass Clustering (SPC) Algorithm is proposed. …”
    Get full text
    Get full text
    Conference or Workshop Item
  8. 8

    CC_TRS: continuous clustering of trajectory stream data based on micro cluster life by Abdulrazzaq, Musaab Riyadh, Mustapha, Norwati, Sulaiman, Md. Nasir, Mohd Sharef, Nurfadhlina

    Published 2017
    “…For offline phase, a density based clustering approach is used to generate macro clusters depending on temporal micro clusters. …”
    Get full text
    Get full text
    Get full text
    Article
  9. 9

    Balancing exploration and exploitation in ACS algorithms for data clustering by Jabbar, Ayad Mohammed, Sagban, Rafid, Ku-Mahamud, Ku Ruhana

    Published 2019
    “…The performance of the proposed algorithm is compared with that of several common clustering algorithms using real-world datasets. …”
    Get full text
    Get full text
    Get full text
    Article
  10. 10

    Cluster optimization in VANET using MFO algorithm and K-Means clustering by Ramlee, Sham Rizal, Hasan, Sazlinah, K. Subramaniam, Shamala

    Published 2023
    “…Overall, the MFO Algorithm and K-Means algorithm can be used in combination to optimize the clustering in VANET, leading to better network performance, more reliable communication, and improved efficiency.…”
    Get full text
    Get full text
    Conference or Workshop Item
  11. 11

    Clustering Methods For Cluster-Based Routing Protocols In Wireless Sensor Networks: Comparative Study by Hassan, Ali Abdul Hussian, Md Shah, Wahidah, Jabbar Mohammed, Ali Abdul, Othman, Mohd Fairuz Iskandar

    Published 2017
    “…So, the energy-efficient routing protocols are very necessary and considers vital task for sensors networks. Various approaches of clustering algorithms are used to optimize the energy of routing protocols. …”
    Get full text
    Get full text
    Get full text
    Article
  12. 12

    USING LATENT SEMANTIC INDEXING FOR DOCUMENT CLUSTERING by MUFLIKHAH, LAILIL

    Published 2010
    “…Document clustering is an implementation of data mining task. …”
    Get full text
    Get full text
    Thesis
  13. 13

    An adaptive density-based method for clustering evolving data streams / Amineh Amini by Amini, Amineh

    Published 2014
    “…This study proposes a density-based algorithm for clustering evolving data streams. The proposed method, which is called MuDi-Stream (Multi Density clustering algorithm for evolving data Stream), is an online-offline algorithm with four main components. …”
    Get full text
    Get full text
    Get full text
    Thesis
  14. 14

    Comparative analysis of K-Means and K-Medoids for clustering exam questions / Nurul Zafirah Mokhtar by Mokhtar, Nurul Zafirah

    Published 2016
    “…This unsupervised learning usually leads to undirected knowledge discovery. The cluster detection algorithm searches for clusters of data which are similar to one another by using similarity measures. …”
    Get full text
    Get full text
    Thesis
  15. 15

    Clustering natural language morphemes from EEG signals using the Artificial Bee Colony algorithm by Sulaiman, Suriani, Ahmed Yahya, Saba, Mohd Shukor, Nur Sakinah, Ismail , Amelia Ritahani, Zaahirah, Qazi, Yaacob, Hamwira, Abdul Rahman, Abdul Wahab, Dzulkifli, Mariam Adawiah

    Published 2015
    “…Using as input the features extracted from EEG signals during morphological priming tasks, our experimental results indicate that applying the ABC algorithm on EEG datasets to cluster Malay morphemes produces promising results.…”
    Get full text
    Get full text
    Proceeding Paper
  16. 16

    Extracting feature from images by using K-Means clustering algorithm / Abdul Hakim Zainal Abidin by Zainal Abidin, Abdul Hakim

    Published 2016
    “…This research scope are to develop a computer application that can extract meaningful information in images by implement KMeans clustering algorithm 10 self capture facial image will be use as the research subject to test the algorithm that will extracting meaningful information of the person. …”
    Get full text
    Get full text
    Thesis
  17. 17

    GF-CLUST: A nature-inspired algorithm for automatic text clustering by Mohammed, Athraa Jasim, Yusof, Yuhanis, Husni, Husniza

    Published 2016
    “…Text clustering is a task of grouping similar documents into a cluster while assigning the dissimilar ones in other clusters.A well-known clustering method which is the K-means algorithm is extensively employed in many disciplines.However, there is a big challenge to determine the number of clusters using K-means. …”
    Get full text
    Get full text
    Get full text
    Article
  18. 18

    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
    “…Then, the mapping percentages between the predefined and produced clusters are used to assess the performance of the proposed algorithm. …”
    Get full text
    Get full text
    Article
  19. 19

    A customized non-exclusive clustering algorithm for news recommendation systems by Ibrahim, Hamidah, Sidi, Fatimah, Mustapha, Aida, Darvishy, Asghar

    Published 2019
    “…In this paper, we propose a new non-exclusive clustering algorithm named Ordered Clustering (OC) with the aim is to increase the accuracy of news recommendation for online users. …”
    Get full text
    Get full text
    Get full text
    Article
  20. 20

    OPTIMIZED MIN-MIN TASK SCHEDULING ALGORITHM FOR SCIENTIFIC WORKFLOWS IN A CLOUD ENVIRONMENT by Murad S.S., Badeel R., Alsandi N.S.A., Alshaaya R.F., Ahmed R.A., Muhammed A., Derahman M.

    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. …”
    Review