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Yao Qin, Yiping Shi, Xinze Hao and Jin Liu
Microblog is an important platform for mining public opinion, and it is of great value to conduct emotional analysis of microblog texts during the current epidemic. Aiming at the problem that most current emotional classification methods cannot effective...
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Achintya Kumar Sarkar and Zheng-Hua Tan
Deep representation learning has gained significant momentum in advancing text-dependent speaker verification (TD-SV) systems. When designing deep neural networks (DNN) for extracting bottleneck (BN) features, the key considerations include training targ...
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Kaustubh Mani Tripathi, Pooja Kamat, Shruti Patil, Ruchi Jayaswal, Swati Ahirrao and Ketan Kotecha
This research paper focuses on developing an effective gesture-to-text translation system using state-of-the-art computer vision techniques. The existing research on sign language translation has yet to utilize skin masking, edge detection, and feature e...
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Vladimir Barakhnin, Olga Kozhemyakina and Irina Grigorieva
This paper presents the study of the author?s style of A.S. Pushkin based on the comparison of his poetic texts with the texts of contemporary poets. The purpose of this study is to determine the features of the author?s style of A.S. Pushkin using machi...
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Ana Me?trovic, Milan Petrovic and Slobodan Beliga
Retweet prediction is an important task in the context of various problems, such as information spreading analysis, automatic fake news detection, social media monitoring, etc. In this study, we explore retweet prediction based on heterogeneous data sour...
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Yosra Didi, Ahlam Walha and Ali Wali
In March 2020, the World Health Organisation declared that COVID-19 was a new pandemic. This deadly virus spread and affected many countries in the world. During the outbreak, social media platforms such as Twitter contributed valuable and massive amount...
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Ke Zhao, Lan Huang, Rui Song, Qiang Shen and Hao Xu
Short text classification is an important problem of natural language processing (NLP), and graph neural networks (GNNs) have been successfully used to solve different NLP problems. However, few studies employ GNN for short text classification, and most ...
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Jie Long, Zihan Li, Qi Xuan, Chenbo Fu, Songtao Peng and Yong Min
The opinion recognition for comments in Internet media is a new task in text analysis. It takes comment statements as the research object, by learning the opinion tendency in the original text with annotation, and then performing opinion tendency recogni...
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Jiwon Hong, Dongho Jeong and Sang-Wook Kim
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Zheren Yan, Can Yang, Lei Hu, Jing Zhao, Liangcun Jiang and Jianya Gong
Geocoding is an essential procedure in geographical information retrieval to associate place names with coordinates. Due to the inherent ambiguity of place names in natural language and the scarcity of place names in textual data, it is widely recognized...
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Xieling Chen, Haoran Xie, Gary Cheng, Leonard K. M. Poon, Mingming Leng and Fu Lee Wang
Natural language processing (NLP) is an effective tool for generating structured information from unstructured data, the one that is commonly found in clinical trial texts. Such interdisciplinary research has gradually grown into a flourishing research f...
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Bagus Setya Rintyarna, Riyanarto Sarno and Chastine Fatichah
The growth of ecommerce has triggered online reviews as a rich source of product information. Revealing consumer sentiment from the reviews through Sentiment Analysis (SA) is an important task of online product review analysis. Two popular approaches of ...
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Pingshan Liu, Qi Liang and Zhangjing Cai
Aiming at addressing the inability of traditional web technologies to effectively respond to Winter-Olympics-related user questions containing multiple intentions, this paper explores a multi-model fusion-based multi-intention recognition model BCNBLMATT...
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Hua Yang, Shuxiang Zhang, Hao Shen, Gexiang Zhang, Xingquan Deng, Jianglin Xiong, Li Feng, Junxiong Wang, Haifeng Zhang and Shenyang Sheng
Text classification is one of the fundamental tasks in natural language processing and is widely applied in various domains. CNN effectively utilizes local features, while the Attention mechanism performs well in capturing content-based global interactio...
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Tahir Mehmood, Ivan Serina, Alberto Lavelli, Luca Putelli and Alfonso Gerevini
Biomedical named entity recognition (BioNER) is a preliminary task for many other tasks, e.g., relation extraction and semantic search. Extracting the text of interest from biomedical documents becomes more demanding as the availability of online data is...
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Yi Liang, Turdi Tohti and Askar Hamdulla
In the existing false information detection methods, the quality of the extracted single-modality features is low, the information between different modalities cannot be fully fused, and the original information will be lost when the information of diffe...
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Yousif A. Alhaj, Abdelghani Dahou, Mohammed A. A. Al-qaness, Laith Abualigah, Aaqif Afzaal Abbasi, Nasser Ahmed Obad Almaweri, Mohamed Abd Elaziz and Robertas Dama?evicius
We propose a novel text classification model, which aims to improve the performance of Arabic text classification using machine learning techniques. One of the effective solutions in Arabic text classification is to find the suitable feature selection me...
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Zhen Sun and Xinfu Li
Named entity recognition can deeply explore semantic features and enhance the ability of vector representation of text data. This paper proposes a named entity recognition method based on multi-head attention to aim at the problem of fuzzy lexical bounda...
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Companies have realized the importance of “big data” in creating a sustainable competitive advantage, and user-generated content (UGC) represents one of big data’s most important sources. From blogs to social media and online reviews, c...
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Girma Neshir, Andreas Rauber and Solomon Atnafu
Topic Modeling is a statistical process, which derives the latent themes from extensive collections of text. Three approaches to topic modeling exist, namely, unsupervised, semi-supervised and supervised. In this work, we develop a supervised topic model...
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