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Titlebook: Big Data and Artificial Intelligence; 11th International C Vikram Goyal,Naveen Kumar,Dhruv Kumar Conference proceedings 2023 The Editor(s)

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https://doi.org/10.1007/978-3-540-34351-6 Constructing citations is often time-consuming, requiring researchers to delve into extensive literature and grapple with articulating relevant content. To address this challenge, the field of citation text generation (CTG) has emerged. However, while earlier methods have primarily centered on crea
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Data Mining Trends and Knowledge Discovery,C models possess limitations as they primarily concentrate on single sentences, neglecting the significance of contextual understanding in error correction. While a few models have begun to factor in context alongside target sentences, they frequently depend on inflexible boundaries, which leads to
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,Data Mining: an Introduction – Case Study, model probabilistic dependence between variables. In classical bayesian networks, performing exact as well as approximate inferences are NP-Hard. Quantum circuit developed to represent bayesian network can be used to perform inference, but it is prone to quantum noise and strictly limited by the ma
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Data Warehousing, Data Mining, and OLAP,kers. The timely and efficient detection of road cracks is of utmost importance for maintenance and mitigating further deterioration. Currently, existing techniques to identify cracks entail physical examinations rather than deploying automated image-based techniques, which leads to costly and labor
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https://doi.org/10.1007/978-3-319-50017-1sk such as hate speech detection. In this work, we compare the explainability capabilities of three post-hoc methods on the HateXplain benchmark with different .. Our research is the first work to evaluate the effectiveness of Layerwise Relevance Propagation (LRP) as a post-hoc method for fine-tuned
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Big Data and Artificial Intelligence978-3-031-49601-1Series ISSN 0302-9743 Series E-ISSN 1611-3349
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