An overview on XML similarity : background, current trends and future directions by Tekli, Joe

“…In recent years, XML has been established as a major means for information management, and has been broadly utilized for complex data representation (e.g. multimedia objects). …”
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A hybrid approach for XML similarity by Tekli, Joe

“…In the past few years, XML has been established as an effective means for information management, and has been widely exploited for complex data representation. Owing to an unparalleled increasing use of the XML standard, developing efficient techniques for comparing XML-based documents becomes essential in information retrieval (IR) research. …”
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Leveraging Network Traffic Byte-Streams for Machine Learning Based Early Botnet Attack Detection by Rajesh Thomas

“…However, they require complex data preprocessing and feature extraction which can affect the early detection of botnet attacks. …”
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Effect of Big Data and Analytics on Managing Projects by El Khatib, Mounir

“…Analytic methods and technologies are heavily employed in the management and analysis of large and complex data sets for use in a wide range of applications that enhance the performance of a business. …”
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An Overview on XML Semantic Disambiguation from Unstructured Text to Semi-Structured Data: Background, Applications, and Ongoing Challenges by Tekli, Joe

“…Since the last two decades, XML has gained momentum as the standard for web information management and complex data representation. Also, collaboratively built semi-structured information resources, such as Wikipedia, have become prevalent on the Web and can be inherently encoded in XML. …”
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Drone Detection with Improved Precision in Traditional Machine Learning and Less Complexity in Single Shot Detectors by Kassab, Mohamad

“…It was evident that those techniques are not suitable for complex data sets (sets with several non-drone objects and clutter in the background). …”
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Meta-Heuristic Algorithm-Tuned Neural Network for Breast Cancer Diagnosis Using Ultrasound Images by Ahila A (18394806)

“…Over the decade, numerous artificial neural network (ANN)-based techniques were adopted in order to diagnose and classify breast cancer due to the unique characteristics of learning key features from complex data via a training process. However, these schemes have limitations like slow convergence and longer training time. …”

Cancerous and Non-Cancerous MRI Classification Using Dual DCNN Approach by Zubair Saeed (19325647)

“…Unlike traditional machine learning methods requiring manual feature extraction, DL models are adept at handling complex data like MRIs and excel in classification tasks, making them well-suited for medical image analysis applications. …”