ORCID Profile
0000-0001-7523-9487
Current Organisations
Hunan University
,
Deakin University
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Publisher: Public Library of Science (PLoS)
Date: 09-08-2018
Publisher: Emerald
Date: 19-02-2018
Abstract: Sentiment identification of Chinese text faces many challenges, such as requiring complex preprocessing steps, preparing various word dictionaries carefully and dealing with a lot of informal expressions, which lead to high computational complexity. A method based on Chinese characters instead of words is proposed. This method represents the text into a fixed length vector and introduces the chi-square statistic to measure the categorical sentiment score of a Chinese character. Based on these, the sentiment identification could be accomplished through four main steps. Experiments on corpus with various themes indicate that the performance of proposed method is a little bit worse than existing Chinese words-based methods on most texts, but with improved performance on short and informal texts. Especially, the computation complexity of the proposed method is far better than words-based methods. The proposed method exploits the property of Chinese characters being a linguistic unit with semantic information. Contrasting to word-based methods, the computational efficiency of this method is significantly improved at slight loss of accuracy. It is more sententious and cuts off the problems resulted from preparing predefined dictionaries and various data preprocessing.
Publisher: Elsevier BV
Date: 08-2023
Publisher: ACM
Date: 16-12-2022
Publisher: Elsevier BV
Date: 03-2020
Publisher: Elsevier BV
Date: 05-2023
Publisher: Springer Science and Business Media LLC
Date: 02-10-2022
Publisher: Springer International Publishing
Date: 2022
Publisher: Informa UK Limited
Date: 31-10-2018
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2022
Publisher: Elsevier BV
Date: 2022
Publisher: Modestum Publishing Ltd
Date: 25-11-2017
Publisher: Hindawi Limited
Date: 2014
DOI: 10.1155/2014/262384
Abstract: One of the main differences between sentiment and infectious diseases is that the former one has two opposite infectious states: positive (optimistic) and negative (pessimistic), while the latter one has not. In this paper, based on the SISa model, we consider this issue and propose a new model of sentiment contagion called the SOSa-SPSa model. The results of both numerical and agent-based simulations show that our model could explain the process of sentiment contagion better than that of Hill et al. (2010). Further analysis shows that both the numbers of optimistic and pessimistic in iduals will increase with the probability of spontaneity or contagion and decrease with the probability of recovery. Potential applications of this model in financial market have also been discussed.
Publisher: Springer Science and Business Media LLC
Date: 16-02-2021
Publisher: Elsevier BV
Date: 02-2022
Publisher: Hindawi Limited
Date: 2014
DOI: 10.1155/2014/539230
Abstract: With the development of the Chinese interest rate market, SHIBOR is playing an increasingly important role. Based on principal component analysing SHIBOR, a two-factor Vasicek model is established to portray the change in SHIBOR with different terms. And parameters are estimated by using the Kalman filter. The model is also used to fit and forecast SHIBOR with different terms. The results show that two-factor Vasicek model fits SHIBOR well, especially for SHIBOR in terms of three months or more.
Publisher: Association for Computing Machinery (ACM)
Date: 15-09-2023
DOI: 10.1145/3609503
Abstract: The Internet of Things (IoT) and Distributed ledger technology (DLT) have significantly changed our daily lives. Due to their distributed operational environment and naturally decentralized applications, the convergence of these two technologies indicates a more lavish arrangement for the future. This article develops a comprehensive survey to investigate and illustrate state-of-the-art DLT for various IoT use cases, from smart homes to autonomous vehicles and smart cities. We develop a novel framework for conducting a systematic and comprehensive review of DLT over IoT by extending the knowledge graph approach. With relevant insights from this review, we extract innovative and pragmatic techniques to DLT design that enable high-performance, sustainable, and highly scalable IoT systems. Our findings support designing an end-to-end IoT-native DLT architecture for the future that fully coordinates network-assisted functionalities.
Location: United States of America
No related grants have been discovered for Qiujun Lan.