...Jinzhu Zhang; Haoyu Li; Ying Ye; Qiuyue Wang Purpose This paper aims to propose a method based on multi-source data and deep learning to early identify emerging technologies (ETs). On the one hand, this paper considers sufficient data sources related to the key characteristics of ETs, which can...

... lexicons. Our approach involves a systematic methodology for refining sentiment scores in WordNet synsets (groups of words that share the same meaning in a specific context) that relies on lexicons, machine learning, deep learning and large language models (LLMs). More precisely, we trained several models...

... The proposed architecture uses neighborhood and dependency tree-based relations for target opinion extraction, a domain–ontology-based knowledge management system for aspect term extraction, and deep learning techniques for classification. Findings The authors use different deep learning architectures...

...Yi-Hung Liu; Sheng-Fong Chen Purpose Whether automatically generated summaries of health social media can assist users in appropriately managing their diseases and ensuring better communication with health professionals becomes an important issue. This paper aims to develop a novel deep learning...

... 2021 Emerald Publishing Limited Licensed re-use rights only Knowledge acquisition Entity relation extraction Cross-lingual Deep learning Generative adversarial network With the advent of the big data era, organization of knowledge, information and data is facing great challenges...

...Wang Leilei; Sowmipriya Rajendiran; K. Gayathri Purpose The main goal of the physical education (PE) environment is that each individual trained should achieve self-fulfillment with the large group of students involved with their own efforts. Deep learning is applying transferrable knowledge...

... advantages in both efficiency and accuracy for pedestrian detection task. It contributes to both data preprocessing for person re-identification and the research on deep learning. The recent revival of neural networks with a deep structure has marked new advances in pattern recognition and computer vision...