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12th International Conference of Information and Communication Technology, ICTech 2023

作者： Chen, Xueliang Liu, Tianming Tang, Gongzheng Liu, Yunjiang Shenyang Institute of Computing Technology Chinese Academy of Sciences University of Chinese Academy of Sciences Beijing China Shenyang Institute of Computing Technology Chinese Academy of Sciences University of Chinese Academy of Sciences Shandong University Laboratory of Big Data and Artificial Intelligence Technology Beijing China

ISBN: (纸本)9798350332919

With the continuous popularization of medical informatization, the number of medical documents, medical guides, electronic medical records and other medical texts shows a trend of rapid growth and huge scale. Medical texts contain great social value. However, most medical texts exist in an unstructured form and cannot be directly applied to products. Therefore, how to fully explore the potential valuable information has become a hot research direction in the field of natural language processing. Named entity recognition is the basic task of natural language processing, and also the key task of medical data mining and analysis. It also lays the foundation for downstream tasks such as medical term relationship extraction and medical term standardization. Named entity recognition aims to find some key phrases in a large number of texts, such as people's names, place names, diseases and drugs. At present, named entity recognition has made great achievements in the open field, but there are still many problems in the research of named entity recognition in the medical field, such as the strong professionalism of entities, the long length of some types of entities, and the existence of complex entities mixed in Chinese and English. Aiming at the problem that the length of named entities in existing medical electronic medical records is longer than that in other fields, resulting in low extraction accuracy, a named entity recognition algorithm based on boundary enhancement is proposed. The model adopts the method of multi-task learning, which can effectively alleviate the boundary problem caused by the length of medical terms. We have tried various models on our medical electronic medical record data set. Experimental results show that this method is simple and effective in medical named entity recognition. © 2023 IEEE.

关键词： data mining

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Design of Teaching Model for Intuitive Imagination Development Supported by NetPad 17th

Design of Teaching Model for Intuitive Imagination Developme...

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17th International Conference on Computer Science and Education, ICCSE 2022

作者： Gao, Jinghui Li, Jing Wang, Jie Zhou, Qixin Zhang, Chuanjun Guan, Hao Institute of Computing Science and Technology Guangzhou University Guangzhou China Department of Teaching Leshan Normal University Chengdu China School of Mathematics and Big Data Guizhou Education University Guiyang China

ISBN: (纸本)9789819924455

As one of the core literacies in mathematics, intuitive imagination is essential in learning geometry in middle school. Recently, BOPPPS, which is a teaching model that featured clear objectives, has gradually become an effective course design model for cultivating students’ intuitive imagination. Meanwhile, NetPad is a browser-based dynamic mathematical software that supports online mathematical experiments and dynamically displays geometric changes. In this paper, we propose a model called N-BOPPPS, which combines advantages of the BOPPPS teaching model and NetPad, aiming at developing students’ intuitive imagination. This model consists of six procedures supported by NetPad, i.e., bridge-in, objective, pre-assessment, participatory learning, post-assessment, and summary. It supports classroom instructions such as the inquiry-based model and student-engaged model. Besides, it encourages students to carry out experimental investigations and innovative practice during the learning process, and then their intuitive imagination is improved. At last, teaching practice is conducted under the guidance of N-BOPPPS and the effectiveness of this model is verified. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Students

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RAUIE: A Relation-Augmented Document-Level Event Extraction Model Based on UIE 5

RAUIE: A Relation-Augmented Document-Level Event Extraction ...

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5th International Seminar on Artificial Intelligence, Networking and Information Technology, AINIT 2024

作者： Liang, Yiyuan Jia, Hong Wang, Licai Huang, Yangchen Yang, Zhe Big Data Research and Development Center North China Institute of Computing Technology Beijing China Tsinghua University Department of Computer Science and Technology Beijing China The Chinese University of Hong Kong Department of Computer Science and Engineering Hong Kong

ISBN: (纸本)9798350385557

In document-level event extraction tasks, multiple event types often coexist within a document (the multi-event problem), and arguments may play different roles across different events (the argument intertwining problem). Existing methods often suffer from significantly reduced event extraction accuracy, mainly when focusing on scenarios with scarce annotated data and imbalanced event-type distributions. This paper emphasizes enhancing the correlation between event triggers and arguments to address these challenges. Therefore, we propose the Relation-Augmented UIE Model (RADIE), which introduces entity relationships into prompts using prompt-based learning and designs a relation-augmentation algorithm to improve the accuracy and completeness of event extraction. Experimental results demonstrate that this approach significantly outperforms baseline methods, mainly showcasing excellent performance on datasets with long-tail distributions. © 2024 IEEE.

关键词： document-level event extraction relation augment Universal Information Extraction

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Review of Model-Based Techniques in Augmented Reality Occlusion Handling 1st

Review of Model-Based Techniques in Augmented Reality Occlus...

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1st International Conference on Expert Clouds and Applications, ICOECA 2023

作者： Ahmad, Muhammad Anwar Suaib, Norhaida Mohd Ismail, Ajune Wanis ViCubeLab Faculty of Computing Universiti Teknologi Malaysia Johor81310 Malaysia UTM Big Data Center Ibnu Sina Institute of Scientific and Industrial Research Universiti Teknologi Malaysia Johor81310 Malaysia

ISBN: (纸本)9789819917440

This paper reviews a model-based method in occlusion handling. The common methods of handling occlusion in Augmented Reality (AR) can be generally classified as depth-based or model-based. This paper presents a review of model-based methods in order to gain understanding of the current state-of-the-art literature and challenges in this field. After searching and filtering in SCOPUS database, 7 papers ranging from 2015 to 2022 were selected for this review and analyzed. From the review, the main conclusion that can be drawn is the trend evolved from researching and developing on the Kinect device to handheld devices. The main challenges are improving the lighting interaction between real and virtual objects and also reducing misalignment due to reprojection errors. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Augmented reality

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Study of Raising Students Level of Geometric Understanding with the Aid of Technology 23

Study of Raising Students Level of Geometric Understanding w...

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7th International Conference on Education and Multimedia Technology, ICEMT 2023

作者： Chen, Yuanhua Rao, Ailing Xu, Zhonglan Zhang, Chuanjun Guan, Hao Institute of Computing Science and Technology Guangzhou University China The Second Primary School of Zixi The Second Primary School of Zixi China School of Mathematics and Big Data Guizhou Education University Guiyang China

ISBN: (纸本)9798400709142

The ultimate goal of learning mathematics is mathematical understanding, which is why it is so important in mathematics education. It is critical to categorize the degrees of geometric understanding because geometry is both an important and challenging subject in secondary school mathematics. In this essay, the meaning of the term "geometric understanding"is defined along with the concept of "mathematical understanding"and related theories. The level of geometric understanding is divided into five categories: intuition, abstraction, connection, inventing, and civilizing. The geometry teaching strategy supported by NetPad is suggested to foster students' geometric understanding. It consists of five parts: Creating Situations and Posing Questions - Imagining, Exploring and Abstracting, Analyzing - Transferring and Connecting - Varying and Innovating - Appreciating Geometry and Penetrating Culture. Through examples, the precise operational procedure of the teaching strategy based on NetPad to advance students' geometric understanding is also covered. © 2023 ACM.

关键词： Geometry

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Real-Time Food Simulation Using Real Hand Gesture for Malaysia Cultural Heritage 1

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3rd International Conference on Advanced computing and Intelligent Technologies, ICACIT 2023

作者： Ismail, Anita Fairos Ismail, Ajune Wanis Fadzli, Fazliaty Edora Shuib, Norhaida Mohd Mixed and Virtual Reality Research Lab ViCubeLab Faculty of Computing Universiti Teknologi Malaysia Johor81310 Malaysia UTM Big Data Center Ibnu Sina Institute of Scientific and Industrial Research Universiti Teknologi Malaysia Johor81310 Malaysia

ISBN: (数字)9789819719617

ISBN: (纸本)9789819719600

Virtual Reality (VR) thrives on interactivity, and recent strides in this domain emphasize the role of gesture interaction. This study delves into the immersive realm of hand gestures, designed to liberate VR users from conventional controllers like mice or keyboards. The primary aim is to explore the application of these gestures in preserving and perpetuating the traditional culinary heritage of Pulut Panggang, a revered dish in Malaysian culture. Pulut Panggang, considered intangible heritage, holds cultural significance that transcends generations, particularly among the youth. The study meticulously examines hand gesture movements tailored to emulate the traditional cooking techniques associated with Pulut Panggang. This includes gestures for spatula control, forward and backward motions simulating the rolling of rice, and lateral movements replicating the use of a bamboo fan for grilling the rice rolls. Emphasizing authenticity, the simulation adheres to traditional methodologies, employing customary tools and materials. This approach serves as a poignant means of preserving the essence of traditional cooking methods within the VR environment. By seamlessly integrating hand gesture controls into the simulation, users are guided through the six crucial steps involved in crafting Pulut Panggang. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Virtual reality

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Towards Long-term Fairness in Interactive Recommendation: A Maximum Entropy Reinforcement Learning Approach

Towards Long-term Fairness in Interactive Recommendation: A ...

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2023 IEEE International Conference on Web Services, ICWS 2023

作者： Shi, Xiaoyu Liu, Quanliang Xie, Hong Shang, Mingsheng Chongqing Institute of Green and Intelligent Technology Chinese Academy of Sciences Chongqing Key Laboratory of Big Data and Intelligent Computing Chongqing China University of Chinese Academy of Sciences Chongqing School Chongqing China

ISBN: (纸本)9798350304855

This paper considers the problem of maintaining the long-term fairness of item exposure in interactive recommendation systems under the dynamic setting that user preference and item popularity evolve over time. The challenge is that the evolving dynamics of user preference and item popularity in the feedback loop amplify the long-term 'unfairness' of item exposure. To address this challenge, we first formulate a constrained Markov Decision Process (MDP) to capture evolving dynamics of user preference. The proposed constrained MDP imposes long-term fairness requirements via maximum entropy techniques. Moreover, to illuminate the 'unfairness' amplifying effect caused by the evolving dynamic of item popularity in the feedback loop, we design a debiased reward function to eliminate popularity bias in the training data. To this end, the proposed framework can maintain acceptable recommendation accuracy while exposing items as randomly as possible, ensuring long-term benefits for users. Experiments on three datasets demonstrate the effectiveness and superiority of our proposed framework in terms of recommendation performance and fairness. © 2023 IEEE.

关键词： Reinforcement learning

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Complex-Cycle-Consistent Diffusion Model for Monaural Speech Enhancement

arXiv

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arXiv 2024年

作者： Li, Yi Sun, Yang Angelov, Plamen School of Computing and Communications Lancaster University United Kingdom Big Data Institute University of Oxford United Kingdom

In this paper, we present a novel diffusion model-based monaural speech enhancement method. Our approach incorporates the separate estimation of speech spectra’s magnitude and phase in two diffusion networks. Throughout the diffusion process, noise clips from real-world noise interferences are added gradually to the clean speech spectra and a noise-aware reverse process is proposed to learn how to generate both clean speech spectra and noise spectra. Furthermore, to fully leverage the intrinsic relationship between magnitude and phase, we introduce a complex-cycle-consistent (CCC) mechanism that uses the estimated magnitude to map the phase, and vice versa. We implement this algorithm within a phase-aware speech enhancement diffusion model (SEDM). We conduct extensive experiments on public datasets to demonstrate the effectiveness of our method, highlighting the significant benefits of exploiting the intrinsic relationship between phase and magnitude information to enhance speech. The comparison to conventional diffusion models demonstrates the superiority of SEDM. Copyright © 2024, The Authors. All rights reserved.

关键词： Speech enhancement

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Hierarchical Multiview Top-k Pooling with Deep-Q-Networks

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2024年第6期5卷 2985-2996页

作者： Li, Zhi-Peng Su, Hai-Long Wu, Yong- Zhang, Qin-Hu Yuan, Chang-An Gribova, Valeriya Filaretov, Vladimir Fedorovich Huang, De-Shuang Eastern Institute of Technology Zhejiang Ningbo315201 China University of Science and Technology of China School of Life Sciences Anhui Hefei230026 China Tongji University Institute of Machine Learning and Systems Biology School of Electronics and Information Engineering Shanghai201804 China Guangxi Academy of Sciences Institute of Big Data and Intelligent Computing Research Center Nanning530007 China Far Eastern Branch of the Russian Academy of Sciences Institute of Automation and Control Processes Vladivostok690041 Russia

Graph neural networks (GNNs) are extensions of deep neural networks to graph-structured data. It has already attracted widespread attention for various tasks such as node classification and link prediction. Existing research focuses more on graph convolutional neural networks (GCNs). However, it is usually overlooked that graph pooling can obtain graph representations by summarizing and down-sampling node information. Meanwhile, existing graph pooling methods mainly use top-k for node selection, but most of them consider only single view information when scoring nodes, and the k values in top-k are usually selected empirically. This work proposes the hierarchical multiview top-k pooling (HMTPool) with deep-Q-networks, which scores nodes taking into account multiview information (considering graph structure and features) and does not rely on the empirical adaptive selection of the best k value. HMTPool is a two-stage process. It first uses a variant GCN and multilayer perceptron to score the nodes from structural and feature perspectives, respectively and then performs fusion operations on the multiview information scores of the nodes. In addition, to select the optimal pooling ratio of top-k, we propose a deep-Q-network-based top-k (DTop-k) node selection method, which can adaptively select the best pooling ratio without prior knowledge. Experimental results on six TUdatasets and two Benchmarking GNNs datasets demonstrate the effectiveness of our proposed approach. © 2020 IEEE.

关键词： Convolution

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A Review on data Quality Dimensions for big data 7

A Review on Data Quality Dimensions for Big Data

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7th Information Systems International Conference, ISICO 2023

作者： Ridzuan, Fakhitah Zainon, Wan Mohd Nazmee Wan Faculty of Data Science and Computing Universiti Malaysia Kelantan Pengkalan Chepa Kelantan Kota Bharu16100 Malaysia Institute for Artificial Intelligence & Big Data Universiti Malaysia Kelantan Pengkalan Chepa Kelantan Kota Bharu16100 Malaysia School of Computer Sciences Universiti Sains Malaysia Penang11800 Malaysia

big data wave has led to a rapid increase in the amount of data being collected by organizations. While the accuracy and reliability of prediction models are often prioritized, the quality of the collected data is frequently overlooked. Poor data quality can result in the common problem of ‘garbage in, garbage out'. Traditional measures of data quality, such as accuracy, consistency, completeness, and timeliness, are no longer adequate in the era of big data. Therefore, this paper proposes a taxonomy of data quality dimensions specifically for big data, addressing emerging challenges by formulating 20 dimensions and categorizing them into four distinct categories. © 2023 The Authors. Published by Elsevier B.V.

关键词： Information management

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