Search Results - (( structure representation mining algorithm ) OR ( java implication based algorithm ))

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  1. 1
    Compact structure representation in discovering frequent patterns for association rules

    Compact structure representation in discovering frequent patterns for association rules by Mustapha, Norwati, Sulaiman, Md. Nasir, Othman, Mohamed, Selamat, Mohd Hasan

    Published 2002
    “…This paper presents a compact structure representation called Flex-tree in discovering frequent patterns for association rules. …”
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  2. 2
    Compact structure representation in discovering frequent patterns for association rules

    Compact structure representation in discovering frequent patterns for association rules by Mustapha, N., Sulaiman, M.N., Othman, M., Selamat, M.H.

    Published 2002
    “…This paper presents a compact structure representation called Flex-tree in discovering frequent patterns for association rules. …”
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  3. 3
    Frequent itemset mining in high dimensional data: a review

    Frequent itemset mining in high dimensional data: a review by Md. Zaki, Fatimah Audah, Zulkurnain, Nurul Fariza

    Published 2019
    “…In addition, it reviews many techniques used in several algorithms that make frequent itemset mining more efficient. …”
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  4. 4
    Enhanced ontology-based text classification algorithm for structurally organized documents

    Enhanced ontology-based text classification algorithm for structurally organized documents by Oleiwi, Suha Sahib

    Published 2015
    “…This research combines the ontology and text representation for classification by developing five algorithms. …”
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  5. 5
    Scalable approach for mining association rules from structured XML data

    Scalable approach for mining association rules from structured XML data by Abazeed, Ashraf Riad, Mamat, Ali, Sulaiman, Md. Nasir, Ibrahim, Hamidah

    Published 2009
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  6. 6
    Mining association rules from structured XML data

    Mining association rules from structured XML data by Abazeed, Ashraf Riad, Mamat, Ali, Sulaiman, Md. Nasir, Ibrahim, Hamidah

    Published 2009
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  7. 7
    Dissimilarity algorithm on conceptual graphs to mine text outliers

    Dissimilarity algorithm on conceptual graphs to mine text outliers by Kamaruddin, Siti Sakira, Hamdan, Abdul Razak, Abu Bakar, Azuraliza, Mat Nor, Fauzias

    Published 2009
    “…The graphical text representation method such as Conceptual Graphs (CGs) attempts to capture the structure and semantics of documents.As such, they are the preferred text representation approach for a wide range of problems namely in natural language processing, information retrieval and text mining.In a number of these applications, it is necessary to measure the dissimilarity (or similarity) between knowledge represented in the CGs.In this paper, we would like to present a dissimilarity algorithm to detect outliers from a collection of text represented with Conceptual Graph Interchange Format (CGIF).In order to avoid the NP-complete problem of graph matching algorithm, we introduce the use of a standard CG in the dissimilarity computation.We evaluate our method in the context of analyzing real world financial statements for identifying outlying performance indicators.For evaluation purposes, we compare the proposed dissimilarity function with a dice-coefficient similarity function used in a related previous work.Experimental results indicate that our method outperforms the existing method and correlates better to human judgements. …”
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  8. 8
    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
    “…Another aim of this study is to do an enhancement on the current structure of FLEX algorithm in terms of elimination of the candidate generation step. …”
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  9. 9
    Combining data mining algorithm and object-based image analysis for detailed urban mapping of hyperspectral images

    Combining data mining algorithm and object-based image analysis for detailed urban mapping of hyperspectral images by Hamedianfar, Alireza, Mohd Shafri, Helmi Zulhaidi, Mansor, Shattri, Ahmad, Noordin

    Published 2014
    “…The high accuracy of object-based classification can be linked to the knowledge discovery produced by the DM algorithm. This algorithm increased the productivity of OBIA, expedited the process of attribute selection, and resulted in an easy-to-use representation of a knowledge model from a decision tree structure.…”
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  10. 10
    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
    “…Therefore, the present study aims: (1) to improve Indonesian text summary by enhancing the Sequence of Word (SoW) as text representation using Sequential Pattern Mining (SPM) with PrefixSpan algorithm since the effectiveness of SPM in Indonesian is proven useful for text classification and clustering; (2) to combine SPM and Deep Learning (DeepSPM) in text summarization with Indonesian text, as a result of its superior accuracy when trained with large amounts of data; and (3) to evaluate the readability of Indonesian text summary with several evaluation scenarios. …”
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  11. 11
    Feature-based approach and sequential pattern mining to enhance quality of Indonesian automatic text summarization

    Feature-based approach and sequential pattern mining to enhance quality of Indonesian automatic text summarization by Maylawati, Dian Sa’adillah, Jaya Kumar, Yogan, Kasmin, Fauziah

    Published 2023
    “…Therefore, this research aims to enhance the quality of extractive Indonesian automatic text summarization with considering the quality of structured representation of text. This research uses sequential pattern mining (SPM) to produce This research use SPM to produce sequence of words (SoW) as structured text representation using PrefixSpan algorithm. …”
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  12. 12
    Image Classification for Age-related Macular Degeneration Screening Using Hierarchical Image Decompositions and Graph Mining

    Image Classification for Age-related Macular Degeneration Screening Using Hierarchical Image Decompositions and Graph Mining by Mohd Hanafi Ahmad Hijazi, Chuntao Jiang, Frans Coenen, Yalin Zheng

    Published 2011
    “…The resulting decomposition is then stored in a tree structure to which a weighted frequent sub-tree mining algorithm is applied. …”
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  13. 13
    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
    “…We employ conceptual graphs interchange format (CGIF) – a knowledge representation formalism to capture the structure and semantics of sentences. …”
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  14. 14
    Evolving fuzzy grammar for crime texts categorization

    Evolving fuzzy grammar for crime texts categorization by Mohd Sharef, Nurfadhlina, Martin, Trevor

    Published 2015
    “…Text mining refers to the activity of identifying useful information from natural language text. …”
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  15. 15
    The implications for ahybrid detection technique against malicious sqlattacks on web applications

    The implications for ahybrid detection technique against malicious sqlattacks on web applications by Bahjat Arif, Sarajaldeen Akram, Wani, Sharyar

    Published 2025
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  16. 16
    Digital Quran With Storage Optimization Through Duplication Handling And Compressed Sparse Matrix Method

    Digital Quran With Storage Optimization Through Duplication Handling And Compressed Sparse Matrix Method by Ashraf Saleh Mohammad Alomoush

    Published 2024
    thesis::doctoral thesis
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  17. 17
    Multitasking deep neural network models for Arabic dialect sentiment analysis

    Multitasking deep neural network models for Arabic dialect sentiment analysis by Alali, Muath Mohammad Oqlah

    Published 2022
    “…NCNN achieves its optimum performance when structured by three convolutional layers. Sensitivity analysis is conducted to evaluate the impact of various combinations of NCNN structural hyperparameters, such as the size of pooling, filters, and the number of convolutional filters on the classification performances. …”
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