2022 14th International Conference on Machine Learning and Computing (ICMLC)最新文献_第6页

Tweet Sentiment Extraction Using Byte Level Pretrained Language Model∗ 基于字节级预训练语言模型的推文情感提取

2022 14th International Conference on Machine Learning and Computing (ICMLC) Pub Date : 2022-02-18 DOI: 10.1145/3529836.3529941

Haowei Liu, Enhao Tan

引用次数: 0

Conditional Generative Adversarial Networks for Hyperspectral Image Classification 高光谱图像分类的条件生成对抗网络

2022 14th International Conference on Machine Learning and Computing (ICMLC) Pub Date : 2022-02-18 DOI: 10.1145/3529836.3529859

Nianze Wu, Bozhi Hao, Jiahao Ma, Tianhong Gao, Yancong Deng

引用次数: 0

Optimization and Reconstruction for EPMA Image Compressed Sensing Based on Chaotic Measurement Matrix 基于混沌测量矩阵的EPMA图像压缩感知优化与重构

2022 14th International Conference on Machine Learning and Computing (ICMLC) Pub Date : 2022-02-18 DOI: 10.1145/3529836.3529846

Li Zhang, Jun Zhang, Anan Jin

引用次数: 0

Chinese NER with High-Level Features in Specific Domain 在特定领域具有高级特征的汉语NER

2022 14th International Conference on Machine Learning and Computing (ICMLC) Pub Date : 2022-02-18 DOI: 10.1145/3529836.3529937

Mengna Nie, Lianglun Cheng, Haiming Ye, Weiwen Zhang

引用次数: 0

An Improved Calibration Method for the Structured Light System Based on Self-correction of Reprojection Error 一种基于重投影误差自校正的结构光系统标定方法

2022 14th International Conference on Machine Learning and Computing (ICMLC) Pub Date : 2022-02-18 DOI: 10.1145/3529836.3529905

Beilei Li, Peng Han, Li Peng, Kaiqing Luo, Dongmei Liu, Jian-jua Qiu

{"title":"An Improved Calibration Method for the Structured Light System Based on Self-correction of Reprojection Error","authors":"Beilei Li, Peng Han, Li Peng, Kaiqing Luo, Dongmei Liu, Jian-jua Qiu","doi":"10.1145/3529836.3529905","DOIUrl":"https://doi.org/10.1145/3529836.3529905","url":null,"abstract":"Structured light 3D reconstruction is widely applied in various fields. During the calibration process of structured light 3D reconstruction, it is very important to raise the calibration accuracy on the parameters of the structured light system. In this paper, we propose a method based on re-projection error self-correction to obtain more accurate corner positions by screening the re-projection error values of DMD images. Experimental results show that this method can improve the calibration accuracy by 64.17%. We also propose an effective standard for the placement of calibration plate, which is of great significance to reduce the number of iterations of the program. According to a series of experiments based on the above standard, the number of iterations of the proposed re-projection error self-correction method is no more than 5 times. It proves that the proposed self-correction method and placement standard are feasible, the calibration process of structured light 3D reconstruction is optimized, and its calibration efficiency is improved.","PeriodicalId":285191,"journal":{"name":"2022 14th International Conference on Machine Learning and Computing (ICMLC)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116955515","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

SRT: Shape Reconstruction Transformer for 3D Reconstruction of Point Cloud from 2D MRI SRT:用于二维MRI点云三维重建的形状重建变压器

2022 14th International Conference on Machine Learning and Computing (ICMLC) Pub Date : 2022-02-18 DOI: 10.1145/3529836.3529902

Bowen Hu, Yanyan Shen, Guocheng Wu, Shuqiang Wang

引用次数: 3

A method of Evaluation for Small and Medium-sized Enterprises 一种中小企业评价方法

2022 14th International Conference on Machine Learning and Computing (ICMLC) Pub Date : 2022-02-18 DOI: 10.1145/3529836.3529901

Zhuang Kui, Xie Yu, W. Wei, Yan Chun Gang

{"title":"A method of Evaluation for Small and Medium-sized Enterprises","authors":"Zhuang Kui, Xie Yu, W. Wei, Yan Chun Gang","doi":"10.1145/3529836.3529901","DOIUrl":"https://doi.org/10.1145/3529836.3529901","url":null,"abstract":"Abstract-Small and medium-sized enterprises (SMEs) have characteristics of small scale of development, poor anti-risk ability, and imperfect management. Timely and accurate evaluation of these enterprises is of great significance to corporate management, market supervision departments and social investors. Existing evaluation methods are mostly based on the internal financial information of mature enterprises, which are not suitable for small and medium-sized enterprises which have not yet achieved revenue capabilities, and have imperfect financial indicators. In this paper, we propose an evaluation model of the development trend of SMEs based on the enterprise knowledge graph. We obtain the information of these enterprises on the financial websites and then use entity recognition and relationship techniques to explore major events and relationships between enterprises, and build enterprise knowledge graph. We construct the feature sets of these enterprises, and use cluster analysis to classify and evaluate the enterprises. A graph-based neural network method is proposed to capture the deeper influence on the development trend among enterprises. The proposed method evaluates the development trend of SMEs from a new perspective.","PeriodicalId":285191,"journal":{"name":"2022 14th International Conference on Machine Learning and Computing (ICMLC)","volume":"68 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129842549","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: 1

Artificial Intelligence Model to Predict the Virality of Press Articles 预测新闻文章病毒式传播的人工智能模型

2022 14th International Conference on Machine Learning and Computing (ICMLC) Pub Date : 2022-02-18 DOI: 10.1145/3529836.3529953

Yesid L. Lopez, D. Grimaldi, Sebastian Garcia, Jonatan Ordoez, Carlos Carrasco-Farré, Andres A. Aristizabal

{"title":"Artificial Intelligence Model to Predict the Virality of Press Articles","authors":"Yesid L. Lopez, D. Grimaldi, Sebastian Garcia, Jonatan Ordoez, Carlos Carrasco-Farré, Andres A. Aristizabal","doi":"10.1145/3529836.3529953","DOIUrl":"https://doi.org/10.1145/3529836.3529953","url":null,"abstract":"Currently, many people share news, links, or videos, without being aware of the impact they can have on people's decisions or ways of acting. A clear example, recently experienced in Colombia, corresponds to the national strike which happened at the time of this research. Due to these unexpected circumstances, colombians experienced the influence news have on decision making that can affect the country, not only economically but politically, and socially. It showed how news can generate fear in people, or even misinform, as is the case of fake news. For these reasons, it is key to determine the relevance a story can have. Predicting the impact, will allow us to pay more attention to those news that can affect people more, avoiding misinformation and fake news. However, the problem is that there is no way of predicting the impact that a press article can have. Therefore, the aim of this work is to implement a machine learning model that allows us to predict, with the best possible accuracy, the virality of online press articles (defining virality as the amount of clicks that an article receives when it is opened). In order to achieve this goal, we followed the CRISP-DM methodology, which focuses on machine learning projects. The best obtained result corresponds to the model where the core of the architecture was based on BERT, a pre-trained model, which, for a pair of press articles headlines, predicted whether the first headline would be more viral than the second one. On the other hand, the evaluation was carried out by comparing the amount of clicks for a pair of articles. For a practitioner point of view, digital marketers can use our results to select the best words for their online marketing campaign. For a theoretical point of view, our results present an innovative natural language processing approach based on one of the best breed of Neural network models (BERT).","PeriodicalId":285191,"journal":{"name":"2022 14th International Conference on Machine Learning and Computing (ICMLC)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129896923","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

Lads: Deep Survival Analysis for Churn Prediction Analysis in the Contract User Domain 契约用户领域流失预测分析的深度生存分析

2022 14th International Conference on Machine Learning and Computing (ICMLC) Pub Date : 2022-02-18 DOI: 10.1145/3529836.3529853

Feng Xu, Hao Zhang, Juan Zheng, Tingxuan Zhao, X. Wang, Zhiquan Zeng

{"title":"Lads: Deep Survival Analysis for Churn Prediction Analysis in the Contract User Domain","authors":"Feng Xu, Hao Zhang, Juan Zheng, Tingxuan Zhao, X. Wang, Zhiquan Zeng","doi":"10.1145/3529836.3529853","DOIUrl":"https://doi.org/10.1145/3529836.3529853","url":null,"abstract":"Survival analysis methods are currently used in the fields of medicine, economics, biology and engineering, and focus on the relationship between covariates and the timing of events. Survival analysis makes such use of survival time that it is better suited to the user domain than other machine learning models, In order to mine information about the user's time-series characteristics, improve the ability of neural networks to process information and the efficiency of network training with large data sets. Based on deep survival analysis, the Lads (LSTM Attention Deep Survival) model was designed to combine Long Short-Term Memory networks and Attention mechanisms to predict the occurrence of events of interest in the contract user domain. The LSTM acts as a feature extractor and performs pre-processing of time-series characteristics information, while the Attention mechanism mainly enhances the interpretability of the model. The final experimental results show that the Lads survival analysis model is a better predictor in the contract user domain than survival analysis methods such as CPH (Cox Proportional Hazard Model) and DeepSurv.","PeriodicalId":285191,"journal":{"name":"2022 14th International Conference on Machine Learning and Computing (ICMLC)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127949124","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

NTP-VFL - A New Scheme for Non-3rd Party Vertical Federated Learning NTP-VFL——一种非第三方垂直联邦学习的新方案

2022 14th International Conference on Machine Learning and Computing (ICMLC) Pub Date : 2022-02-18 DOI: 10.1145/3529836.3529841

Di Zhao, Ming Yao, Wanwan Wang, Hao He, Xin Jin

引用次数: 3