2022 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT)最新文献_第9页

How Severe is Your COVID-19? Predicting SARS-CoV-2 Infection with Graph Attention Capsule Networks 你的COVID-19有多严重?基于图注意力胶囊网络的SARS-CoV-2感染预测

2022 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT) Pub Date : 2022-11-01 DOI: 10.1109/WI-IAT55865.2022.00121

Runjie Zhu, Zhiwen Xie, Guangyou Zhou

{"title":"How Severe is Your COVID-19? Predicting SARS-CoV-2 Infection with Graph Attention Capsule Networks","authors":"Runjie Zhu, Zhiwen Xie, Guangyou Zhou","doi":"10.1109/WI-IAT55865.2022.00121","DOIUrl":"https://doi.org/10.1109/WI-IAT55865.2022.00121","url":null,"abstract":"Recent studies in machine learning have demonstrated the effectiveness of applying graph neural networks (GNNs) to single-cell RNA sequencing (scRNA-seq) data to predict COVID-19 disease states. In this study, we propose a graph attention capsule network (GACapNet) which extracts and fuses Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) transcriptomic patterns to improve node classification performance on cells and genes. Significantly different from the existing GNN approaches, we innovatively incorporate a capsule layer with dynamic routing into our model architecture to combine and fuse gene features effectively and to allow those more prominent gene features present in the output. We evaluate our GACapNet model on two scRNA-seq datasets, and the experimental results show that our GACapNet model significantly outperforms state-of-the-art baseline models. Therefore, our study demonstrates the capability of advanced machine learning models to generate predictive features and evolutionary patterns of the SARS-CoV-2 pathogen, and the applicability of closing knowledge gaps in the pathogenesis and recovery of COVID-19.","PeriodicalId":345445,"journal":{"name":"2022 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114838660","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Characterizing the nature of trust & misinformation on Twitter 描述Twitter上的信任和错误信息的性质

2022 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT) Pub Date : 2022-11-01 DOI: 10.1109/WI-IAT55865.2022.00074

Bryan Boots, S. Simske

引用次数: 0

SMAT: String Matching in Action Theory 动作理论中的字符串匹配

2022 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT) Pub Date : 2022-11-01 DOI: 10.1109/WI-IAT55865.2022.00014

Xing Tan, Jingwei Huang, Yilan Gu

{"title":"SMAT: String Matching in Action Theory","authors":"Xing Tan, Jingwei Huang, Yilan Gu","doi":"10.1109/WI-IAT55865.2022.00014","DOIUrl":"https://doi.org/10.1109/WI-IAT55865.2022.00014","url":null,"abstract":"Software applications in Artificial Intelligence, particularly Natural Language Processing, often need to decide how far two given strings differ from each other in their content. To this day edit distance remains to be widely used for measuring the difference. Symbols in strings are compared, but the meanings of strings are not considered in almost all algorithms based on edit distance. This paper aims to define a logical formalism for comparing strings. Thus the comparisons are enhanced with computer-comprehensible semantics. More precisely, we propose SMAT, a String Matching Action Theory, written in the language of Situation Calculus. We show that SMAT can be used to flexibly represent various string operators. Damerau-Levenshtein edit operators are specifically used as an illustration example. We remark that 1) SMAT is, in addition, a software program implementation for string matching; 2) Knowledge-based heuristics in support of string-matching strategies can be easily incorporated into SMAT, and 3) SMAT provides new opportunities for string matching through automated planning in Artificial Intelligence.","PeriodicalId":345445,"journal":{"name":"2022 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131297547","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Information Sharing among Senior Parents and Children for the Prevention of Frailty Using ICT 高龄父母与子女资讯共享，利用资讯及通讯科技预防脆弱

2022 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT) Pub Date : 2022-11-01 DOI: 10.1109/WI-IAT55865.2022.00110

Daisuke Yasui, Futoshi Ohyama, H. Matsumoto

{"title":"Information Sharing among Senior Parents and Children for the Prevention of Frailty Using ICT","authors":"Daisuke Yasui, Futoshi Ohyama, H. Matsumoto","doi":"10.1109/WI-IAT55865.2022.00110","DOIUrl":"https://doi.org/10.1109/WI-IAT55865.2022.00110","url":null,"abstract":"The composition of households in Japan in recent years has shown that the nuclear family has been progressing, and the number of families (children) who live separately from their senior parents has been increasing. Therefore, it is assumed that it is difficult for family members who do not live together to grasp the health status of the senior citizens at any time. In this study, we developed a system that enables family members living in remote areas to view \"frail-related physical information\" measured from the senior citizens at any time through the use of ICT (Information and Communication Technology). In this study, \"physical information\" refers to frailty-related factors such as body weight and muscle mass measured by a body composition analyzer, and since it is necessary to measure them regularly, we decided to measure them when they use day services. The measured values will be anonymized and stored on a server. Identification data and PWs were given to family members to enable them to obtain information at any time. The ability to confirm physical information as numerical values, rather than only visual or auditory information via telephone or SNS, may help promote family intervention to extend healthy life expectancy.","PeriodicalId":345445,"journal":{"name":"2022 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130660907","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

An Optimized High Dimension Data Reduction Method based on Covariance 一种基于协方差的优化高维数据约简方法

2022 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT) Pub Date : 2022-11-01 DOI: 10.1109/WI-IAT55865.2022.00070

Qiqi Huang, Haolan Zhang, Genlang Chen, Jijun Tong, Sanghyuk Lee

{"title":"An Optimized High Dimension Data Reduction Method based on Covariance","authors":"Qiqi Huang, Haolan Zhang, Genlang Chen, Jijun Tong, Sanghyuk Lee","doi":"10.1109/WI-IAT55865.2022.00070","DOIUrl":"https://doi.org/10.1109/WI-IAT55865.2022.00070","url":null,"abstract":"The advances in the electronic age have made the generation of data faster. However, the speed of data analysis has not kept pace with the growth of data. So people try to transform the large data into small-scale data to improve the efficiency of data analysis. Like data dimension reduction, data sampling and data compression are the most commonly used methods at present. The common sampling methods, including random sampling, stratified sampling, have been utilized extensively in various applications. Furthermore, data dimension reduction methods have been deployed in various areas.This paper proposes an optimized high dimension data reduction method based on covariance. Firstly, calculate the covariance matrix of the original dataset and the sub dataset. Then, create a transformation matrix according to the covariance matrix and use this transformation matrix to get a new dataset. Finally, obtain a new sub dataset by adjusting data from sub dataset and new dataset. This method can generate representative datasets and provide effective solutions for big data processing.","PeriodicalId":345445,"journal":{"name":"2022 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127848800","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Ancient Migration Algorithm: A Behavioral Path Model Study of the Lowest-cost Goal from an Anthropological Perspective 古代移民算法:人类学视角下最低成本目标的行为路径模型研究

2022 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT) Pub Date : 2022-11-01 DOI: 10.1109/WI-IAT55865.2022.00144

Ziyang Weng, Y. Hu, Hui Li, Xiaoyu Tang, Zhimo Weng

引用次数: 0

Adaptive Neighborhood Distribution-based Model for Estimating Helpful Votes of Customer Review 基于自适应邻域分布的顾客评论有益投票估计模型

2022 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT) Pub Date : 2022-11-01 DOI: 10.1109/WI-IAT55865.2022.00029

Ristu Saptono, Tsunenori Mine

{"title":"Adaptive Neighborhood Distribution-based Model for Estimating Helpful Votes of Customer Review","authors":"Ristu Saptono, Tsunenori Mine","doi":"10.1109/WI-IAT55865.2022.00029","DOIUrl":"https://doi.org/10.1109/WI-IAT55865.2022.00029","url":null,"abstract":"The number of helpful votes on a review is an essential indicator of how much impact the review has on other users. Therefore, estimating the number of helpful votes is an important task. Regression analysis and Tobit Modelling are typical methods of prediction. Those methods assume that the number of helpful votes on any dataset follows a normal distribution. However, the assumption is not usually confirmed, and the distribution of the helpful votes often follows other distributions. Consequently, the estimation results might not be entirely appropriate. In addition, the distribution of the helpful votes might change on the dataset as the review size increases. Considering the distribution change, we propose an adaptive neighborhood distribution-based model, which is aware of the neighborhood distribution change. We evaluate our proposed model with time-based sampling methods on review datasets sorted in chronological order and conducted extensive experiments on real-world datasets. Experimental results illustrate that the awareness of changes in the neighborhood distribution has a significant impact on the estimation of helpful votes.","PeriodicalId":345445,"journal":{"name":"2022 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT)","volume":"121 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132313723","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

On using the DIET architecture for sentiment analysis and emotion detection 利用DIET架构进行情感分析和情感检测

2022 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT) Pub Date : 2022-11-01 DOI: 10.1109/WI-IAT55865.2022.00102

M. Arevalillo-Herráez, Pablo Arnau-González, Inés Bravo-Cabrera, N. Ramzan

引用次数: 1

Intelligent Prediction-Intervention approach to Support Students' Success in Web-based Learning Environments: A Case Study in Higher Education 支持学生在网络学习环境中取得成功的智能预测干预方法:以高等教育为例

2022 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT) Pub Date : 2022-11-01 DOI: 10.1109/WI-IAT55865.2022.00044

Tesnim Khelifi, N. Rabah, Ibtissem Daoudi, B. L. Grand, F. Ktata

{"title":"Intelligent Prediction-Intervention approach to Support Students' Success in Web-based Learning Environments: A Case Study in Higher Education","authors":"Tesnim Khelifi, N. Rabah, Ibtissem Daoudi, B. L. Grand, F. Ktata","doi":"10.1109/WI-IAT55865.2022.00044","DOIUrl":"https://doi.org/10.1109/WI-IAT55865.2022.00044","url":null,"abstract":"Due to the COVID-19 pandemic, the demand for distance learning has significantly increased in higher education institutions. This type of learning is usually supported by Web-based learning systems such as Massive Open Online Courses (Coursera, edX, etc.) and Learning Management Systems (Moodle, Blackboard-Learn, etc.). However, in this remote context, students often lack feedback and support from educational staff, especially when they face difficulties or challenges. For that reason, this work presents a Prediction-Intervention approach that (a) predicts students who present difficulties during an online learning course, based on two main learning indicators, namely engagement and performance rates, and (b) offers immediate support to students, tailored to the problem they are facing. To predict students’ issues, our approach considers ten machine learning algorithms of different types (standalone, ensemble, and deep learning) which are compared to determine the best performing ones. It has been experimented with a dataset collected from the Blackboard-Learn platform utilized in an engineering school called ESIEE-IT in France during 2021-2022 academic year, showing thus quite promising results.","PeriodicalId":345445,"journal":{"name":"2022 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131754455","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Predicting the Score of Atomic Candidate OWL Class Axioms 预测原子候选OWL类公理的分数

2022 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT) Pub Date : 2022-11-01 DOI: 10.1109/WI-IAT55865.2022.00020

Ali Ballout, A. Tettamanzi, C. Pereira

引用次数: 0