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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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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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Tulsi Patel, Mark W. Jones and Thomas Redfern
We present a novel approach to providing greater insight into the characteristics of an unlabelled dataset, increasing the efficiency with which labelled datasets can be created. We leverage dimension-reduction techniques in combination with autoencoders...
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Sardar Parhat, Mutallip Sattar, Askar Hamdulla and Abdurahman Kadir
In this study, based on a morpheme segmentation framework, we researched a text keyword extraction method for Uyghur, Kazakh and Kirghiz languages, which have similar grammatical and lexical structures. In these languages, affixes and a stem are joined t...
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Lei Gao, Lijuan Zhang, Lei Zhang and Jie Huang
With the explosive growth in short texts on the Web and an increasing number of Web corpora consisting of short texts, short texts are playing an important role in various Web applications. Entity linking is a crucial task in knowledge graphs and a key t...
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Fadi Dornaika and Abdelmalik Moujahid
Facial Beauty Prediction (FBP) is an important visual recognition problem to evaluate the attractiveness of faces according to human perception. Most existing FBP methods are based on supervised solutions using geometric or deep features. Semi-supervised...
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Giuseppe Granato, Alessio Martino, Andrea Baiocchi and Antonello Rizzi
Network traffic analysis, and specifically anomaly and attack detection, call for sophisticated tools relying on a large number of features. Mathematical modeling is extremely difficult, given the ample variety of traffic patterns and the subtle and vari...
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Nilufa Yeasmin, Nosin Ibna Mahbub, Mrinal Kanti Baowaly, Bikash Chandra Singh, Zulfikar Alom, Zeyar Aung and Mohammad Abdul Azim
The novel coronavirus disease (COVID-19) has dramatically affected people?s daily lives worldwide. More specifically, since there is still insufficient access to vaccines and no straightforward, reliable treatment for COVID-19, every country has taken th...
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Yaohui Hu, Chun Liu, Zheng Li, Junkui Xu, Zhigang Han and Jianzhong Guo
Buildings are important entity objects of cities, and the classification of building shapes plays an indispensable role in the cognition and planning of the urban structure. In recent years, some deep learning methods have been proposed for recognizing t...
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Hanlin Sun, Wei Jie, Jonathan Loo, Liang Chen, Zhongmin Wang, Sugang Ma, Gang Li and Shuai Zhang
Presently, data that are collected from real systems and organized as information networks are universal. Mining hidden information from these data is generally helpful to understand and benefit the corresponding systems. The challenges of analyzing such...
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