检索结果-内蒙古大学图书馆

1st International Conference on data science and Artificial Intelligence, DSAI 2023

作者： Lhasiw, Nunthawat Tanantong, Tanatorn Sanglerdsinlapachai, Nuttapong Thammasat Research Unit in Data Innovation and Artificial Intelligence Department of Computer Science Faculty of Science and Technology Thammasat University Pathum Thani Thailand Strategic Analytics Networks with Machine Learning and AI Research Team National Electronics and Computer Technology Center Pathum Thani Thailand

ISBN: (纸本)9789819979684

Chatbot platforms, e.g., Facebook and Line, have revolutionized human interaction in the digital age. In order to develop an automatic chatbot classification, there are several challenges especially for Thai chat messages. Conversational messages are usually short and ambiguous. Therefore, it is difficult to find a dataset for constructing an effective classification model. To address the limited size of the dataset, data augmentation techniques can be possibly applied. data augmentation involves generating synthetic messages by applying various transformations to existing data samples while preserving their original meaning. In this study, the size and diversity of the dataset is increased by two methods, i.e., text augmentation using word2vec from Thai2Fit and English-Thai machine translation models proposed by VISTEC. Based on the augmented messages, a Deep Learning technique, BiLSTM, is used to construct a chatbot classification model. The experimental obtained results demonstrate that data augmentation can help to increase the classification performance. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd 2023.

关键词： Classification (of information)

来源：评论

学校读者我要写书评

暂无评论

Image Fusion Using Wavelet Transformation and XGboost Algorithm

引用

computers, Materials & Continua 2024年第4期79卷 801-817页

作者： Shahid Naseem Tariq Mahmood Amjad Rehman Khan Umer Farooq Samra Nawazish Faten S.Alamri Tanzila Saba Department of Information Sciences Division of S&TUniversity of EducationLahore54770Pakistan Artificial Intelligence and Data Analytics(AIDA)Lab CCIS Prince Sultan UniversityRiyadh11586Saudi Arabia Faculty of Information Sciences University of EducationVehari CampusVehari61100Pakistan Department of Computer Science University of Engineering and TechnologyTaxila47050Pakistan Department of Mathematical Sciences College of SciencePrincess Nourah Bint Abdulrahman UniversityRiyadh84428Saudi Arabia

Recently,there have been several uses for digital image *** fusion has become a prominent application in the domain of imaging *** create one final image that provesmore informative and helpful compared to the original input images,image fusion merges two or more initial images of the same *** fusion aims to produce,enhance,and transform significant elements of the source images into combined images for the sake of human visual *** fusion is commonly employed for feature extraction in smart robots,clinical imaging,audiovisual camera integration,manufacturing process monitoring,electronic circuit design,advanced device diagnostics,and intelligent assembly line robots,with image quality varying depending on *** research paper presents various methods for merging images in spatial and frequency domains,including a blend of stable and curvelet transformations,everageMax-Min,weighted principal component analysis(PCA),HIS(Hue,Intensity,Saturation),wavelet transform,discrete cosine transform(DCT),dual-tree Complex Wavelet Transform(CWT),and multiple wavelet *** fusion methods integrate data from several source images of an identical target,thereby enhancing information in an extremely efficient *** precisely,in imaging techniques,the depth of field constraint precludes images from focusing on every object,leading to the exclusion of certain *** tackle thess challanges,a very efficient multi-focus wavelet decomposition and recompositionmethod is *** use of these wavelet decomposition and recomposition techniques enables this method to make use of existing optimized wavelet code and filter *** simulated outcomes provide evidence that the suggested approach initially extracts particular characteristics from images in order to accurately reflect the level of clarity portrayed in the original *** study enhances the performance of the eXtreme Gradient Boosting(XGBoos

关键词： Image fusion max-min average CWT XGBoost DCT inclusive innovations spatial and frequency domain

来源：评论

学校读者我要写书评

暂无评论

Conversation Sentiment Analysis in League of Legends Game Community

Conversation Sentiment Analysis in League of Legends Game Co...

引用

Cybernetics and Innovations (ICCI), International Conference on

作者： Thutchaphong Pongkhan Phutanate Khoosirirat Pokpong Songmuang Rachada Kongkachandra Data Science and Innovation College of Interdisciplinary Studies Thammasat University Thailand Department of Computer Science Faculty of Science and Technology Thammasat University Thailand

ISBN: (数字)9798350370096

ISBN: (纸本)9798350370102

Gaming communities are groups of people from different nations, religions, genders, and ages who come to play games and have discussions about the games. However, some gaming communities are plagued by toxic behavior of people in communities, which negatively affects to other players. A Conversation Sentiment Analysis in the League of Legends Game Community is about analyzing the toxicity of the League of Legends game community by using the Sentiment Analysis methods which have Bag-of-Words and Weight Score method, and then comparing it with three machine learning techniques: Logistic Regression, Support Vector Machine (SVM), and CatBoost, and showing how members in this community have interacted with other members in the community by using the Conversation Mapping Interactive method.

关键词： Support vector machines Sentiment analysis Humanities Technological innovation Logistic regression Toxicology Social networking (online)

来源：评论

学校读者我要写书评

暂无评论

Deep Convolutional Neural Network Approach for COVID-19 Detection

引用

computer Systems science & Engineering 2022年第7期42卷 201-211页

作者： Yu Xue Bernard-Marie Onzo Romany F.Mansour Shoubao Su School of Computer and Software Nanjing University of Information Science and TechnologyNanjing210044China Engineering Research Center of Digital Forensics Ministry of EducationNanjing University of Information Science and TechnologyNanjingChina Department of Mathematics Faculty of ScienceNew Valley UniversityEl-Kharja72511Egypt Jiangsu Key Laboratory of Data Science and Smart Software Jinling Institute of TechnologyNanjing211169China

Coronavirus disease 2019(Covid-19)is a life-threatening infectious disease caused by a newly discovered strain of the *** by the end of 2020,Covid-19 is still not fully understood,but like other similar viruses,the main mode of transmission or spread is believed to be through droplets from coughs and sneezes of infected *** accurate detection of Covid-19 cases poses some questions to scientists and *** two main kinds of tests available for Covid-19 are viral tests,which tells you whether you are currently infected and antibody test,which tells if you had been infected ***-tine Covid-19 test can take up to 2 days to complete;in reducing chances of false negative results,serial testing is *** image processing by means of using Chest X-ray images and Computed Tomography(CT)can help radiologists detect the *** imaging approach can detect certain characteristic changes in the lung associated with *** this paper,a deep learning model or tech-nique based on the Convolutional Neural Network is proposed to improve the accuracy and precisely detect Covid-19 from Chest Xray scans by identifying structural abnormalities in scans or X-ray *** entire model proposed is categorized into three stages:dataset,data pre-processing andﬁnal stage being training and classiﬁcation.

关键词： COVID-19 deep learning convolutional neural network X-ray

来源：评论

学校读者我要写书评

暂无评论

Twin Transition or Competing Interests? Validation of the Artificial Intelligence and Sustainability Perceptions Inventory (AISPI)

arXiv

引用

arXiv 2025年

作者： Bush, Annika Research Center Trustworthy Data Science and Security University Alliance Ruhr Faculty of Computer Science Technical University Dortmund Dortmund Germany

As artificial intelligence (AI) and sustainability initiatives increasingly intersect, understanding public perceptions of their relationship becomes crucial for successful implementation. However, no validated instrument exists to measure these specific perceptions. This paper presents the development and validation of the Artificial Intelligence and Sustainability Perceptions Inventory (AISPI), a novel 13-item instrument measuring how individuals view the relationship between AI advancement and environmental sustainability. Through factor analysis (N = 105), we identified two distinct dimensions: ‘Twin Transition’ and ‘Competing Interests’. The instrument demonstrated strong reliability (α = .89) and construct validity through correlations with established measures of AI and sustainability attitudes. Our findings suggest that individuals can simultaneously recognize both synergies and tensions in the AI-sustainability relationship, offering important implications for researchers and practitioners working at this critical intersection. This work provides a foundational tool for future research on public perceptions of AI’s role in sustainable development. © 2025, CC BY-NC-ND.

关键词： Sustainable development goals

来源：评论

学校读者我要写书评

暂无评论

SepLL: Separating Latent Class Labels from Weak Supervision Noise

SepLL: Separating Latent Class Labels from Weak Supervision ...

引用

2022 Findings of the Association for Computational Linguistics: EMNLP 2022

作者： Stephan, Andreas Kougia, Vasiliki Roth, Benjamin Research Group Data Mining and Machine Learning Faculty of Computer Science University of Vienna Vienna Austria UniVie Doctoral School Computer Science Vienna Austria Faculty of Philological and Cultural Studies University of Vienna Vienna Austria

In the weakly supervised learning paradigm, labeling functions automatically assign heuristic, often noisy, labels to data samples. In this work, we provide a method for learning from weak labels by separating two types of complementary information associated with the labeling functions: information related to the target label and information specific to one labeling function only. Both types of information are reflected to different degrees by all labeled instances. In contrast to previous works that aimed at correcting or removing wrongly labeled instances, we learn a branched deep model that uses all data as-is, but splits the labeling function information in the latent space. Specifically, we propose the end-to-end model SepLL which extends a transformer classifier by introducing a latent space for labeling function specific and task-specific information. The learning signal is only given by the labeling functions matches, no pre-processing or label model is required for our method. Notably, the task prediction is made from the latent layer without any direct task signal. Experiments on Wrench text classification tasks show that our model is competitive with the state-of-the-art, and yields a new best average performance. © 2022 Association for Computational Linguistics.

关键词： Classification (of information)

来源：评论

学校读者我要写书评

暂无评论

The Gulf of Interpretation: From Chart to Message and Back Again

arXiv

引用

arXiv 2023年

作者： Knoll, Christian Möller, Torsten Gregory, Kathleen Koesten, Laura Faculty of Computer Science Doctoral School Computer Science University of Vienna Austria Faculty of Computer Science Data Science @ Uni Vienna University of Vienna Austria Centre for Science and Technology Studies Leiden University Netherlands Faculty of Computer Science University of Vienna Austria

Charts are used to communicate data visually, but often, we do not know whether a chart’s intended message aligns with the message readers perceive. In this mixed-methods study, we investigate how data journalists encode data and how members of a broad audience engage with, experience, and understand these visualizations. We conducted workshops and interviews with school and university students, job seekers, designers, and senior citizens to collect perceived messages and feedback on eight real-world charts. We analyzed these messages and compared them to the intended message. Our results help to understand the gulf that can exist between messages (that producers encode) and viewer interpretations. In particular, we find that consumers are often overwhelmed with the amount of data provided and are easily confused with terms that are not well known. Chart producers tend to follow strong conventions on how to visually encode particular information that might not always benefit consumers. Copyright © 2023, The Authors. All rights reserved.

关键词： data visualization

来源：评论

学校读者我要写书评

暂无评论

A privacy preserving data aggregation and query for metro passenger flow via mobile crowdsensing

A privacy preserving data aggregation and query for metro pa...

引用

作者： Zhang, Yuanyuan Ying, Zuobin Zhao, Bowen Chen, Chun Lung Philip School of Computer Science and Engineering South China University of Technology Guangzhou China Faculty of Data Science City University of Macau China Guangzhou Institute of Technology Xi'dian University Guangzhou China Pazhou Lab Guangzhou China

With the popularity of mobile Internet networks and mobile terminal equipment, mobile crowdsensing (MCS) has become a popular and economical way of data collection, sharing, and query services. However, the existing privacy-preserving query schemes MCS-based less consider the sensing user's privacy leakage at data aggregation phase and querier's privacy leakage at query service phase simultaneously. In this article, we propose a novel privacy-preserving aggregation and query scheme applied in metro passenger flow via MCS, which achieves the metro passenger flow acquisition and query service and protects the sensing user's identity and location privacy as well as the querier's query privacy. We exploit Paillier cryptosystem and pseudonym mechanism to prevent the privacy leakage, and utilize secure kNN algorithm to protect the query privacy. Meanwhile, we achieve the sensing user accountability based on digital signature algorithm and credible management. The privacy analysis demonstrates that our scheme satisfies the privacy-preserving and security requirements. The performance evaluation and experimental result show the efficiency of our scheme in practice. © 2022 John Wiley & Sons, Ltd.

关键词： Privacy-preserving techniques

来源：评论

学校读者我要写书评

暂无评论

Optimal Structure Exploration of Bayesian Network Based on Dealing with the Route Choice Model 6

Optimal Structure Exploration of Bayesian Network Based on D...

引用

6th International Conference on computer Information science and Application Technology, CISAT 2023

作者： Wang, Ziyi Zeng, Yufei Wang, Rui College of Big Data and Intelligent Engineering Southwest Forestry University Kunming China College of Computer Science and Technology Harbin Institute of Technology Yichun China Faculty of Information Engineering and Automation Kunming University of Science and Technology Kunming China

ISBN: (纸本)9781510668546

Route selection in residents' travel is a key link in travel decision-making in transportation systems. In existing studies, discrete choice models are often used to describe residents' travel path choices. However， with today's highly developed big data, the traditional discrete choice model is too simple to represent residents' travel path choices, ignoring the connection between various factors. Therefore, a big data-driven approach is proposed to solve this problem in this paper. Driven by research data and with the introduction of the Bayesian network model, the paper adopts a hill-climbing search strategy to improve the search efficiency, uses a variety of scoring functions to train data, which optimizes the Bayesian network structure. The experimental results show that the model fully considers the causation between the independent variables, which is more logical and makes the construction of the resident travel route selection model more accurate and efficient. © 2023 SPIE.

关键词： Bayesian networks

来源：评论

学校读者我要写书评

暂无评论

Developing a Singlish Neural Language Model using ELECTRA 14

Developing a Singlish Neural Language Model using ELECTRA

引用

14th International Conference on Advanced computer science and Information Systems, ICACSIS 2022

作者： Gotera, Galangkangin Prasojo, Radityo Eko Isal, Yugo Kartono Universitas Indonesia Faculty of Computer Science Depok Indonesia Pitik Digital Indonesia Data & Ai Team Jakarta Indonesia

ISBN: (数字)9781665489362

ISBN: (纸本)9781665489362

We develop and benchmark a Singlish pretrained neural language model. To this end, we build a novel 3 GB Singlish freetext dataset collected through various Singaporean websites. Then, we leverage ELECTRA (Efficiently Learning an Encoder that Classifies Token Replacements Accurately) to train a transformer-based Singlish language model. ELECTRA is chosen due to its resource-efficiency to better ensure reproducibility. We further build two text classification datasets in Singlish: sentiment analysis and language identification. We use the two datasets to fine-tune our ELECTRA model and benchmark the results against other available pretrained models in English and Singlish. Our experiments show that our Singlish ELECTRA model is competitive against the best open-source models we found despite being pretrained within a significantly less amount of time. We publicly release the benchmarking dataset. © 2022 IEEE.

关键词： Sentiment analysis

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：