Search Results - (( data relation _ algorithm ) OR ( java implication based algorithm ))

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

“…Therefore, it is essential to develop a new technique to authenticate access to database related to web applications and prevent SQL injection vulnerabilities. …”
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Digital Quran With Storage Optimization Through Duplication Handling And Compressed Sparse Matrix Method by Ashraf Saleh Mohammad Alomoush

Attribute related methods for improvement of ID3 Algorithm in classification of data: A review by Nur Farahaina, Idris, Mohd Arfian, Ismail

“…Nevertheless, there are some limitations in ID3 algorithm that can affect the performance in the classification of data. …”
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A Theoretical Framework for Big Data Analytics Based on Computational Intelligent Algorithms with the Potential to Reduce Energy Consumption by Chiroma, H., Abdullahi, U.A., Hashem, I.A.T., Saadi, Y., Al-Dabbagh, R.D., Ahmad, M.M., Dada, G.E., Danjuma, S., Maitama, J.Z., Abubakar, A., Abdulhamid, S.�M.

“…In this chapter, we present a theoretical study of energy issues related to applications of computational intelligent algorithms in big data analytics. …”
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Efficient Algorithms to Index, Store and Query XML Documents by Fakhreldin, Mohammed Adam Ibrahim, Khalid, Edris, Jasni, Mohamad Zain, Norrozila, Sulaiman

“…Mapping XML documents into relational database is a promising solution because relational databases are mature and scale very well and they have the advantages that in a relational database XML data and structured data can coexist making it possible to build application that involve both kinds of data with little extra effort. …”
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A theoretical framework for big data analytics based on computational intelligent algorithms with the potential to reduce energy consumption by Haruna, Chiroma, Abdullahi, Usman Ali, Targio Hashem, Ibrahim Abaker, Saadi, Younes, Al-Dabbagh, Rawaa Dawoud, Ahmad, Muhammad Murtala, Emmanuel Dada, Gbenga, Danjuma, Sani, Maitama, Jaafar Zubairu, Abubakar, Adamu, Abdulhamid, Shafi’i Muhammad

“…In this chapter, we present a theoretical study of energy issues related to applications of computational intelligent algorithms in big data analytics. …”
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Dimensionality reduction in data summarization approach to learning relational data by Kheau, Chung Seng, Rayner Alfred, Lau, Hui Keng

“…The DARA algorithm is designed to summarize data and it is one of the approaches introduced in relational data mining in order to handle data with one-to-many relations. …”
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Clustering algorithm for market-basket analysis : the underlying concept of data mining technology by Abdul Kadir, Khairil Annuar

“…In this research, the author tried to relate the algorithm presented with the experiment. …”
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Direct approach for mining association rules from structured XML data by Abazeed, Ashraf Riad

“…There are several techniques to mine association rules from XML data. The basic approach is to map the XML documents to relational data model and to store them in a relational database. …”
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Normalized Relational Storage for Extensible Markup Language (XML) Schema by Kamsuriah, Ahmad, Reduan, Samad

“…Approach: In this study we present an algorithm for generating an optimal design for XML in relational setting. …”
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Constraint preserving mapping algorithm for XML storage by Ahmad, Kamsuriah, Mamat, Ali, Ibrahim, Hamidah, Mohd Noah, Shahrul Azman

“…So it is also useful in information exchange and data integration for preserving the semantics of data originating in XML to relational databases. …”
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Semi-supervised learning for feature selection and classification of data / Ganesh Krishnasamy by Ganesh , Krishnasamy

“…However, these semi-supervised multi-task selection feature algorithms are unable to naturally handle the multi-view data since they are designed to deal with single-view data. …”
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Optimized feature construction methods for data summarizations of relational data by Sze, Florence Sia Fui

“…Dynamic Aggregation of Relational Attributes (DARA) algorithm is one of the approaches to summarize data stored in a target table that has a one-to-many relationship with data stored in a non-target table. …”
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XRecursive, An Efficient Relational Method to Store XML Data by Jasni, Mohamad Zain, K.F., Rabbi, M.A., Ibrahim Fakharaldien, Norrozila, Sulaiman

“…Storing XML documents in a relational database is a promising solution because relational databases are mature and scale very well and they have the advantages that in a relational database XML data and structured data can coexist making it possible to build application that involve both kinds of data with little extra effort . …”
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An ensemble data summarization approach based on feature transformation to learning relational data by Chung, Seng Kheau

“…In the process of summarizing data, the data stored in multi-relational database need to be transformed into Term Frequency - Inverse Document Frequency (TF-IDF) vector space. …”
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Artificial neural network model with different backpropagation algorithms and meteorological data for solar radiation prediction by Heng S.Y., Ridwan W.M., Kumar P., Ahmed A.N., Fai C.M., Birima A.H., El-Shafie A.

Analysis of Chinese patents associated with incremental clustering algorithms: A review / Archana Chaudhari by Chaudhari, Archana, Mulay, Preeti, Kumar Tiwari, Amit

“…This learning is incremental in nature for all involved entities and users, as the data is growing exponentially in real-time. To achieve learning from such dynamic data sources, incremental clustering algorithms are used mandatorily. …”
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Efficient Mapping XML DTD to Relational Database by Mohammed Adam Ibrahim, Fakharaldien, Khalid, Edris, Jasni, Mohamad Zain, Norrozila, Sulaiman

“…Mapping XML documents into relational database is a promising solution because relational databases are mature and scale very well and they have the advantages that in a relational database XML data and structured data can coexist making it possible to build application that involve both kinds of data with little extra effort. …”
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Clustering Student Performance Data Using k-Means Algorithms by Sultan Alalawi, Sultan Juma, Mohd Shaharanee, Izwan Nizal, Mohd Jamil, Jastini

“…Education institutions store large amounts of data regarding students, such as demographics, academic-related data, and student activities. …”
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Multiview Laplacian semisupervised feature selection by leveraging shared knowledge among multiple tasks by Krishnasamy, Ganesh, Paramesran, Raveendran

“…However, these semisupervised multitask selection feature algorithms are unable to naturally handle the multiview data since they are designed to deal single-view data. …”
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