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Abu Shad Ahammed, Aniebiet Micheal Ezekiel and Roman Obermaisser
During an emergency rescue operation, rescuers have to deal with many different health complications like cardiovascular, respiratory, neurological, psychiatric, etc. The identification process of the common health complications in rescue events is not v...
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Muhammad Ali Shafique, Arslan Munir and Joonho Kong
Deep learning is employed in many applications, such as computer vision, natural language processing, robotics, and recommender systems. Large and complex neural networks lead to high accuracy; however, they adversely affect many aspects of deep learning...
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Xiaoping Huang, Yujian Zhou and Yajun Du
In recent years, there has been rapid development in machine learning for solving artificial intelligence tasks in various fields, including translation, speech, and image processing. These AI tasks are often interconnected rather than independent. One s...
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Yu Tong, Weiming Tan, Jingzhi Guo, Bingqing Shen, Peng Qin and Shuaihe Zhuo
In the last decade, blockchain smart contracts emerged as an automated, decentralized, traceable, and immutable medium of value exchange. Nevertheless, existing blockchain smart contracts are not compatible with legal contracts. The automatic execution o...
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Gabriele Papadia, Massimo Pacella and Vincenzo Giliberti
This paper focuses on the automatic analysis of conversation transcriptions in the call center of a customer care service. The goal is to recognize topics related to problems and complaints discussed in several dialogues between customers and agents. Our...
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Ying Zhou, Xiaokang Hu and Vera Chung
Paraphrase detection and generation are important natural language processing (NLP) tasks. Yet the term paraphrase is broad enough to include many fine-grained relations. This leads to different tolerance levels of semantic divergence in the positive par...
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Pin Wu, Rukang Zhu and Zhidan Lei
Using the single premise entailment (SPE) model to accomplish the multi-premise entailment (MPE) task can alleviate the problem that the neural network cannot be effectively trained due to the lack of labeled multi-premise training data. Moreover, the ab...
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Yusuf Sermet and Ibrahim Demir
The COVID-19 pandemic elucidated that knowledge systems will be instrumental in cases where accurate information needs to be communicated to a substantial group of people with different backgrounds and technological resources. However, several challenges...
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Christos Makris, Georgios Pispirigos and Michael Angelos Simos
Text annotation is the process of identifying the sense of a textual segment within a given context to a corresponding entity on a concept ontology. As the bag of words paradigm?s limitations become increasingly discernible in modern applications, severa...
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Sebastião Pais and Gaël Dias
In this work, we present a new unsupervised and language-independent methodology to detect the relations of textual generality. For this, we introduce a particular case of Textual Entailment (TE), namely Textual Entailment by Generality (TEG). TE aims to...
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