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Full-fledged semantic indexing and querying model designed for seamless integration in legacy RDBMS
Published 2018“…We then provide a general keyword query model with specially tailored query processing algorithms built on top of SemIndex, in order to produce semantic-aware results, allowing the user to choose the results' semantic coverage and expressiveness based on her needs. …”
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Combining offline and on-the-fly disambiguation to perform semantic-aware XML querying
Published 2023“…Most methods rely on the concept of Lowest Comment Ancestor (LCA) between two or multiple structural nodes to identify the most specific XML elements containing query keywords posted by the user. Yet, few of the existing approaches consider XML semantics, and the methods that process semantics generally rely on computationally expensive word sense disambiguation (WSD) techniques, or apply semantic analysis in one stage only: performing query relaxation/refinement over the bag of words retrieval model, to reduce processing time. …”
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A Systematic Literature Review on Phishing Email Detection Using Natural Language Processing Techniques
Published 2022“…None of the surveys have ever comprehensively studied the use of Natural Language Processing (NLP) techniques for detection of phishing except one that shed light on the use of NLP techniques for classification and training purposes, while exploring a few alternatives. …”
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Application of Machine Learning Algorithms to Enhance Money Laundering and Financial Crime Detection
Published 2011“…In order to analyze the performance of machine learning algorithms, data was provided by a bank to be used for educational purposes and shall remain undisclosed. …”
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Exploring the Impact of Explainable Artificial Intelligence on Decision-making in Healthcare
Published 2023“…The development of explainable artificial intelligence (XAI) systems, which attempt to give visible and interpretable explanations for AI algorithms' judgements, is a vital part of AI in healthcare. …”
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SemIndex+: A semantic indexing scheme for structured, unstructured, and partly structured data
Published 2018“…We provide a general keyword query model allowing the user to choose the results’ semantic coverage and expressiveness based on her needs. …”
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SemIndex: Semantic-Aware Inverted Index
Published 2017“…We also provide an extended query model and related processing algorithms with the help of SemIndex. …”
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Energy-aware adaptive compression for mobile devices. (c2009)
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Decomposition-based wind power forecasting models and their boundary issue: An in-depth review and comprehensive discussion on potential solutions
Published 2022“…Then, we systematically summarize commonly available boundary issue solutions into three categories, namely algorithm-based solutions, sampling-strategy-based solutions and iteration-based solutions. …”
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Machine Learning–Based Approach for Identifying Research Gaps: COVID-19 as a Case Study
Published 2024“…Furthermore, future studies could evaluate more efficient modeling algorithms, especially those combining topic modeling with statistical uncertainty quantification, such as conformal prediction.…”
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Innovating for the Future Through Technology-Mediated HRM
Published 2024“…With the lack of human managers in certain employment settings (e.g. platform-based gig work), HRM activities are primarily outsourced to algorithmic systems and, in some cases, customers, who engage in performance management processes by submitting anonymous ratings of workers. …”
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Future Prediction of COVID-19 Vaccine Trends Using a Voting Classifier
Published 2021“…Multiple ML algorithms are used to improve decision-making at different aspects after forecasting. …”
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Video surveillance using deep transfer learning and deep domain adaptation: Towards better generalization
Published 2023“…To that end, this paper introduces, to the best of the authors’ knowledge, the first overview of existing DTL- and DDA-based video surveillance to (i) shed light on their benefits, (ii) discuss their challenges, and (iii) highlight their future perspectives.…”
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Con-Detect: Detecting adversarially perturbed natural language inputs to deep classifiers through holistic analysis
Published 2023“…Deep Learning (DL) algorithms have shown wonders in many Natural Language Processing (NLP) tasks such as language-to-language translation, spam filtering, fake-news detection, and comprehension understanding. …”
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Con-Detect: Detecting Adversarially Perturbed Natural Language Inputs to Deep Classifiers Through Holistic Analysis
Published 2023“…<p>Deep Learning (DL) algorithms have shown wonders in many Natural Language Processing (NLP) tasks such as language-to-language translation, spam filtering, fake-news detection, and comprehension understanding. …”