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Clustering of large time-series datasets using a multi-step approach / Saeed Reza Aghabozorgi Sahaf Yazdi by Yazdi, Saeed Reza Aghabozorgi Sahaf

“…Time-series clustering is not only useful as an exploratory technique but also as a subroutine in more complex data mining algorithms. As a result, time-series clustering (as a part of temporal data mining research) has attracted increasing interest for use in various areas such as medicine, biology, finance, economics, and in the Web. …”
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The implications for ahybrid detection technique against malicious sqlattacks on web applications by Bahjat Arif, Sarajaldeen Akram, Wani, Sharyar

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A detailed description on unsupervised heterogeneous anomaly based intrusion detection framework by Udzir, Nur Izura, Hajamydeen, Asif Iqbal

“…More effort has been taken in utilizing the data mining and machine learning algorithms to construct anomaly based intrusion detection systems, but the dependency on the learned models that were built based on earlier network behaviour still exists, which restricts those methods in detecting new or unknown intrusions. …”
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An In-Depth Analysis of Text Clustering Techniques for Identifying Potential Insurance Customers on Social Media: A Machine Learning Perspective by Liew, Chun Kin, Goh, Ching Pang

“…This research focuses on the development of a social media web crawler, coupled with the implementation of sophisticated algorithms like Web Content Mining, Noisy Text Filtering, Named Entity Extraction, Part-Of-Speech (POS) Tagging, and Text Clustering. …”
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An In-Depth Analysis of Text Clustering Techniques for Identifying Potential Insurance Customers on Social Media: A Machine Learning Perspective by Liew, Chun Kin, Goh, Ching Pang

“…This research focuses on the development of a social media web crawler, coupled with the implementation of sophisticated algorithms like Web Content Mining, Noisy Text Filtering, Named Entity Extraction, Part-Of-Speech (POS) Tagging, and Text Clustering. …”
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Digital Quran With Storage Optimization Through Duplication Handling And Compressed Sparse Matrix Method by Ashraf Saleh Mohammad Alomoush