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In this paper, we propose a novel multilevel NER framework, for addressing the challenges of clinical name entity recognition, based on different machine learning and text mining algorithms. The proposed framework, with multiple levels, allows models for increasingly complex NER tasks to be built. The experimental evaluation on two different publicly available datasets, corresponding to different...
Mid-Infrared (MIR) spectroscopy has emerged as the most economically viable technology to determine milk values as well as to identify a set of animal phenotypes related to health, feeding, well-being and environment. However, Fourier transform-MIR spectra incurs a significant amount of redundant data. This creates critical issues such as increased learning complexity while performing Fog and Cloud...
The problem of completing low-tubal-rank tensors from incomplete noisy observations is studied. To recover the underlying tensor, an iterative singular tube thresholding (ISTT) algorithm is proposed. To explore the statistical performance of the proposed algorithm, the estimation error in terms of the Frobenius norm is upper bounded non-asymptotically. The minimax optimal lower bound of the estimation...
Due to the advances of wireless sensor networks, radiofrequency identification (RFID) and Web-based services, large volume of devices have been interconnected to the Internet of Things (IoT). In addition, the tremendous number of IoT services provided by service providers arises an urgent need to propose effective recommendation methods to discover suitable services to users. In this paper, we propose...
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