Search Results - (( java application mining algorithm ) OR ( web navigation using 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
    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
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    Thesis
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  3. 3
    A recommender system approach for classifying user navigation patterns using longest common subsequence algorithm.

    A recommender system approach for classifying user navigation patterns using longest common subsequence algorithm. by Jalali, Mehrdad, Mustapha, Norwati, Sulaiman, Md. Nasir, Mamat, Ali

    Published 2009
    “…The approach is based on the using longest common subsequence algorithm to classify current user activities to predict user next movement. …”
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  4. 4
    Expectation maximization clustering algorithm for user modeling in web usage mining system

    Expectation maximization clustering algorithm for user modeling in web usage mining system by Mustapha, Norwati, Jalali, Manijeh, Jalali, Mehrdad

    Published 2009
    “…Web usage mining algorithms have been widely utilized for modeling user web navigation behavior. …”
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  5. 5
    Separator Database and SPM Tree Framework for Mining Sequential Patterns Using Prefixspan with Pseudoprojection

    Separator Database and SPM Tree Framework for Mining Sequential Patterns Using Prefixspan with Pseudoprojection by Saputra , Dhany, Rambli, Dayang R.A., Foong, Oi Mean

    Published 2008
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  6. 6
    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
    “…There are two main phases in WebPUM; offline phase and online phase. 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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  7. 7
    Adaptive method to improve web recommendation system for anonymous users

    Adaptive method to improve web recommendation system for anonymous users by Almurtadha, Yahya Mohammed

    Published 2011
    “…An enhanced classification algorithm is used to assign the current anonymous user to the best web navigation profile. …”
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  8. 8
    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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  9. 9
    A web usage mining approach based on LCS algorithm in online predicting recommendation systems

    A web usage mining approach based on LCS algorithm in online predicting recommendation systems by Jalali, Mehrdad, Mustapha, Norwati, Sulaiman, Md. Nasir, Mamat, Ali

    Published 2008
    “…To provide online prediction efficiently, we advance an architecture for online predicting in Web Usage Mining system and propose a novel approach based on LCS algorithm for classifying user navigation patterns for predicting users' future requests. …”
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  10. 10
    Study and Implementation of Data Mining in Urban Gardening

    Study and Implementation of Data Mining in Urban Gardening by Mohana, Muniandy, Lee, Eu Vern

    Published 2019
    “…Attached sensors generate data and send these data to the Java Servlet application through a WIFI module. These data are processed and stored in appropriate formats in a MySQL server database. …”
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  11. 11
    Mining Sequential Patterns Using I-PrefixSpan

    Mining Sequential Patterns Using I-PrefixSpan by Dhany , Saputra, Rambli Dayang, R.A., Foong, Oi Mean

    Published 2007
    “…Sequential pattern mining is a relatively new data-mining problem with many areas of application. …”
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  12. 12
    A web-based implementation of k-means algorithms

    A web-based implementation of k-means algorithms by Lee, Quan

    Published 2022
    “…This stinginess of proximity measures in data mining tools is stifling the performance of the algorithm. …”
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    Final Year Project / Dissertation / Thesis
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  13. 13
    Mining Sequential Patterns using I-PrefixSpan

    Mining Sequential Patterns using I-PrefixSpan by Saputra , Dhany, Dayang R.A. Rambli, Foong, Oi Mean

    Published 2008
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    Citation Index Journal
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  14. 14
    Restaurant locator using Djikstra Algorithm / Mohamad Aliff Hakimi Lukman Hakim

    Restaurant locator using Djikstra Algorithm / Mohamad Aliff Hakimi Lukman Hakim by Lukman Hakim, Mohamad Aliff Hakimi

    Published 2017
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  15. 15
    Features selection for intrusion detection system using hybridize PSO-SVM

    Features selection for intrusion detection system using hybridize PSO-SVM by Tabaan, Alaa Abdulrahman

    Published 2016
    “…The simulation will be carried on WEKA tool, which allows us to call some data mining methods under JAVA environment. The proposed model will be tested and evaluated on both NSL-KDD and KDD-CUP 99 using several performance metrics.…”
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  16. 16
    Virtual room decorator in android

    Virtual room decorator in android by Nurul Ain, Ahmed

    Published 2012
    “…Also provides a simulation mobile platform to test and validate different rover chassis design,its navigation and locomotion algorithms,and the support rover operation for the application built.Besides,the comparison with the various related current systems and applications in the web browser and usability of popular mobile application platforms also issued here.…”
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    Undergraduates Project Papers
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  17. 17
    Conference Approval System (e-CoAS) / Nor Hidayah Rahim

    Conference Approval System (e-CoAS) / Nor Hidayah Rahim by Rahim, Nor Hidayah

    Published 2015
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  18. 18
    Sequential pattern mining using personalized minimum support threshold with minimum items

    Sequential pattern mining using personalized minimum support threshold with minimum items by Alias, Suraya, Razali, Mohd Norhisham, Tan, Soo Fun, Sainin, Mohd Shamrie

    Published 2011
    “…The P_minsup is generated for each k-sequence by analyzing the overall support pattern distribution of the click stream data; while the min_i value gives the user the flexibility to gain control on the number of patterns to be generated on the next k-sequence by using the top min_i items. This approach is then applied in the SPADE Algorithm using vector array as an extension from the previous method of using relational database and pre-defined threshold.The result from this experiment demonstrates that P_minsup with the complement of min_i value approach is applicable in assisting the process of determining the suitable threshold value to be used in detecting users' frequent k-sequential topics in navigating the World Wide Web (WWW).…”
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  19. 19
    Prototype development of Web AI-based decision support system: insights and recommendations for satellite anomaly identification

    Prototype development of Web AI-based decision support system: insights and recommendations for satellite anomaly identification by Mutholib, Abdul, Abdul Rahim, Nadirah, Gunawan, Teddy Surya

    Published 2025
    “…This paper also summarizes the key findings of the case studies and discusses the benefits of using a Web AI-based DSS for satellite anomaly identification management. …”
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    Proceeding Paper
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  20. 20
    Dynamic force-directed graph with weighted nodes for scholar network visualization

    Dynamic force-directed graph with weighted nodes for scholar network visualization by Mohd. Aris, Khalid Al-Walid, Ramasamy, Chitra, Mohd Aris, Teh Noranis, Zolkepli, Maslina

    Published 2022
    “…The approach is realized by creating a web-based interface using D3 JavaScript algorithm that allows the visualization to focus on how data are connected to each other more accurately than the conventional lines of data seen in traditional data representation. …”
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