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Florin Leon, Marius Gavrilescu, Sabina-Adriana Floria and Alina Adriana Minea
This paper proposes a classification methodology aimed at identifying correlations between job ad requirements and transversal skill sets, with a focus on predicting the necessary skills for individual job descriptions using a deep learning model. The ap...
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Fan Huang , Nan Yang, Huaming Chen , Wei Bao and Dong Yuan
With the widespread use of end devices, online multi-label learning has become popular as the data generated by users using the Internet of Things devices have become huge and rapidly updated. However, in many scenarios, the user data are often generated...
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Youngki Park and Youhyun Shin
In this paper, we introduce an efficient approach to multi-label image classification that is particularly suited for scenarios requiring rapid adaptation to new classes with minimal training data. Unlike conventional methods that rely solely on neural n...
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Naseer Ahmed Sajid, Atta Rahman, Munir Ahmad, Dhiaa Musleh, Mohammed Imran Basheer Ahmed, Reem Alassaf, Sghaier Chabani, Mohammed Salih Ahmed, Asiya Abdus Salam and Dania AlKhulaifi
Over the decades, a tremendous increase has been witnessed in the production of documents available in digital form. The increased production of documents has gained so much momentum that their rate of production jumps two-fold every five years. These ar...
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Gergely Márk Csányi, Renátó Vági, Andrea Megyeri, Anna Fülöp , Dániel Nagy, János Pál Vadász and István Üveges
Few-shot learning is a deep learning subfield that is the focus of research nowadays. This paper addresses the research question of whether a triplet-trained Siamese network, initially designed for multi-class classification, can effectively handle multi...
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Charalampos M. Liapis and Sotiris Kotsiantis
The use of deep learning in conjunction with models that extract emotion-related information from texts to predict financial time series is based on the assumption that what is said about a stock is correlated with the way that stock fluctuates. Given th...
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Nasir Ayub, Tayyaba, Saddam Hussain, Syed Sajid Ullah and Jawaid Iqbal
Sentiment analysis holds great importance within the domain of natural language processing as it examines both the expressed and underlying emotions conveyed through review content. Furthermore, researchers have discovered that relying solely on the over...
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Yizhou Tan, Wenjing Li, Da Chen and Waishan Qiu
Understanding park events and their categorization offers pivotal insights into urban parks and their integral roles in cities. The objective of this study is to explore the efficacy of Convolutional Neural Networks (CNNs) in categorizing park events thr...
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Muhammad Nadeem, Henry Shen, Lincoln Choy and Julien Moussa H. Barakat
Growing obesity has been a worldwide issue for several decades. This is the outcome of common nutritional disorders which results in obese individuals who are prone to many diseases. Managing diet while simultaneously dealing with the obligations of a wo...
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Dezheng Zhang, Peng Li and Aziguli Wulamu
Profiting from the great progress of information technology, a huge number of multi-label samples are available in our daily life. As a result, multi-label classification has aroused widespread concern. Different from traditional machine learning methods...
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