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mining algorithm » cosine algorithm (توسيع البحث)
method algorithm » mould algorithm (توسيع البحث)
يعرض 21 - 40 نتائج من 329 نتيجة بحث عن '(((( data including algorithm ) OR ( data mining algorithm ))) OR ( elements method algorithm ))', وقت الاستعلام: 0.14s تنقيح النتائج
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    Towards Scalable Process Mining Pipelines حسب Mohamed, Belal

    منشور في 2023
    "…Contributions have covered the spectrum of better algorithms, richer comparison metrics, and movement towards online analysis for process data. …"
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  3. 23

    Indexing Arabic texts using association rule data mining حسب Haraty, Ramzi A.

    منشور في 2019
    "…The model denotes extracting new relevant words by relating those chosen by previous classical methods to new words using data mining rules. Design/methodology/approach The proposed model uses an association rule algorithm for extracting frequent sets containing related items – to extract relationships between words in the texts to be indexed with words from texts that belong to the same category. …"
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    article
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    Customs Trade Facilitation and Compliance for Ecommerce using Blockchain and Data Mining حسب Alqaryouti, Omar

    منشور في 2021
    "…Additionally, the Cross Industry Standard Process for Data Mining (CRISP-DM) methodology is employed for modelling the two proposed clustering algorithms to identify transactional risks. …"
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  6. 26

    The Relation Between Respiratory & Acute Coronary Syndrome Using Data Mining Techniques حسب DOULEH, HANI ABDULLAH YOSEF ABU

    منشور في 2018
    "…In this study I’ve split one dataset of patients who have attended to emergency departments in Abu Dhabi hospitals to two datasets (Respiratory and Cardiac), then applied the data mining algorithms on each dataset and one time on the original dataset. …"
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    Using Educational Data Mining Techniques in Predicting Grade-4 students’ performance in TIMSS International Assessments in the UAE حسب SHWEDEH, FATEN

    منشور في 2018
    "…Educational Data Mining (EDM) is the process of discovering information and relationships from educational data for better understanding of students’ performance, and characteristics of their education providers. …"
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    Variable Selection in Data Analysis: A Synthetic Data Toolkit حسب Mitra, Rohan

    منشور في 2024
    "…Variable (feature) selection plays an important role in data analysis and mathematical modeling. This paper aims to address the significant lack of formal evaluation benchmarks for feature selection algorithms (FSAs). …"
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    article
  14. 34

    Physical optimization algorithms for mapping data to distributed-memory multiprocessors حسب Mansour, Nashat

    منشور في 1992
    "…We also present a technique for efficient mapping of large data sets. The algorithms include a parallel genetic algorithm (PGA), a parallel neural network algorithm (PNN) and a parallel simulated annealing algorithm (PSA). …"
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    masterThesis
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    Properties of simulated annealing and genetic algorithms for mapping data to multicomputers حسب Mansour, Nashat

    منشور في 1997
    "…We experimentally analyze some properties of simulated annealing algorithms (SA) and genetic algorithms (GA) for mapping data to multicomputers. …"
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    article
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    Parallel physical optimization algorithms for allocating data to multicomputer nodes حسب Mansour, Nashat

    منشور في 1994
    "…Three parallel physical optimization algorithms for allocating irregular data to multicomputer nodes are presented. …"
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    article
  18. 38

    Use data Mining Techniques to Predict Users’ Engagement on the Social Network Posts in The Period Before, During and After Ramadan حسب AL RAWASHDEH, HANEEN MOHAMMAD

    منشور في 2017
    "…In this thesis, the effectiveness of using a data mining classifier helps to predict users’ engagement with a social media post before publishing and anticipating the best type of media for the post. …"
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  19. 39

    An enhanced k-means clustering algorithm for pattern discovery in healthcare data حسب Haraty, Ramzi A.

    منشور في 2015
    "…This paper studies data mining applications in healthcare. Mainly, we study k-means clustering algorithms on large datasets and present an enhancement to k-means clustering, which requires k or a lesser number of passes to a dataset. …"
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    article
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