2023 Intelligent Methods, Systems, and Applications (IMSA)最新文献_第2页

An Efficient Deep Learning Approach for Extractive Arabic Text Summarization Based on Multiple Encoders and a Single Decoder 基于多编码器和单解码器的高效深度学习阿拉伯语文本摘要提取方法

2023 Intelligent Methods, Systems, and Applications (IMSA) Pub Date : 2023-07-15 DOI: 10.1109/IMSA58542.2023.10217361

Asmaa H. Elsaid, Ammar Mohammed, L. Fattouh, M. Sakre

{"title":"An Efficient Deep Learning Approach for Extractive Arabic Text Summarization Based on Multiple Encoders and a Single Decoder","authors":"Asmaa H. Elsaid, Ammar Mohammed, L. Fattouh, M. Sakre","doi":"10.1109/IMSA58542.2023.10217361","DOIUrl":"https://doi.org/10.1109/IMSA58542.2023.10217361","url":null,"abstract":"The amount of textual content produced has grown dramatically over the last few thousand years, creating a wealth of information for analysis and knowledge extraction. Daily textual data’s increasing volume and complexity, including social media posts, news articles, emails, and text messages, make consuming and processing all the information difficult. This also means manually sifting through large volumes of text to find relevant information can be time-consuming and difficult. Text summarizing addresses this challenge by automatically condensing text into a more concise format so that users can quickly and easily access the most critical information. In today’s data-driven environment, it has become an essential tool used in multiple contexts, including text analysis, content-based recommendations, and information retrieval. The paper presents a novel extractive Arabic text summarization approach in a single-document framework. The proposed method utilizes a Modified Sequence-to-Sequence (MSTS) algorithm, which incorporates multi-layer encoders and a single-layer decoder into the sequence-to-sequence model. A new Arabic benchmark dataset called HASD is also introduced, which contains 43k articles with their extractive and abstractive summaries. To assess the accuracy of the generated summaries, the authors introduce a new evaluation measure called eval_summary. This measure aids in identifying the most accurate summary from the multiple summarizations produced by the model. The proposed model is tested on the proposed HASD and EASC benchmarks and evaluated using Rouge, Bleu. The experimental results show satisfactory results compared to state-of-the-art methods.","PeriodicalId":110239,"journal":{"name":"2023 Intelligent Methods, Systems, and Applications (IMSA)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128399183","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

End of Session (7) 会议结束(7)

2023 Intelligent Methods, Systems, and Applications (IMSA) Pub Date : 2023-07-15 DOI: 10.1109/imsa58542.2023.10217525

引用次数: 0

Depression Detection from Social Media Platforms: A Systematic Literature Review 社交媒体平台的抑郁检测:系统文献综述

2023 Intelligent Methods, Systems, and Applications (IMSA) Pub Date : 2023-07-15 DOI: 10.1109/IMSA58542.2023.10217763

Abdelmoniem Helmy, Radwa Nassar, Nagy Ramadan

引用次数: 0

Recurrent Neural Networks (RNNs) to improve EEG-based person identification 递归神经网络(RNNs)改进基于脑电图的人识别

2023 Intelligent Methods, Systems, and Applications (IMSA) Pub Date : 2023-07-15 DOI: 10.1109/IMSA58542.2023.10217750

Youssef Mohamed, A. Anter, A. B. Zaky

引用次数: 0

ANER: Arabic and Arabizi Named Entity Recognition using Transformer-Based Approach 基于变换方法的阿拉伯语和阿拉伯语命名实体识别

2023 Intelligent Methods, Systems, and Applications (IMSA) Pub Date : 2023-07-15 DOI: 10.1109/IMSA58542.2023.10217635

Abdelrahman Boda Sadallah, Omar Ahmed, Shimaa S. Mohamed, Omar Hatem, Doaa Hesham, A. Yousef

{"title":"ANER: Arabic and Arabizi Named Entity Recognition using Transformer-Based Approach","authors":"Abdelrahman Boda Sadallah, Omar Ahmed, Shimaa S. Mohamed, Omar Hatem, Doaa Hesham, A. Yousef","doi":"10.1109/IMSA58542.2023.10217635","DOIUrl":"https://doi.org/10.1109/IMSA58542.2023.10217635","url":null,"abstract":"One of the main tasks of Natural Language Processing (NLP), is Named Entity Recognition (NER). It is used in many applications and also can be used as an intermediate step for other tasks. We present ANER, a web-based named entity recognizer for the Arabic, and Arabizi languages. The model is built upon BERT, which is a transformer-based encoder. It can recognize 50 different entity classes, covering various fields. We trained our model on the WikiFANE_Gold dataset which consists of Wikipedia articles. We achieved an F1 score of 88.7%, which beats CAMeL Tools’ F1 score of 83% on the ANERcorp dataset, which has only 4 classes. We also got an F1 score of 77.7% on the NewsFANE Gold dataset which contains out-of-domain data from News articles. The system is deployed on a user-friendly web interface that accepts users’ inputs in Arabic, or Arabizi. It allows users to explore the entities in the text by highlighting them. It can also direct users to get information about entities through Wikipedia directly. We added the ability to do NER using our model, or CAMeL Tools’ model through our website. ANER is publicly accessible at http://www.aner.online. We also deployed our model on HuggingFace at https://huggingface.co/boda/ANER, to allow developers to test and use it.","PeriodicalId":110239,"journal":{"name":"2023 Intelligent Methods, Systems, and Applications (IMSA)","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130263231","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

End of Session (13) 会议结束(十三)

2023 Intelligent Methods, Systems, and Applications (IMSA) Pub Date : 2023-07-15 DOI: 10.1109/imsa58542.2023.10217637

引用次数: 0

Comparative Analysis: Deep vs. Machine Learning for Early DFU Detection in Medical Imaging 对比分析：医学影像中早期 DFU 检测的深度学习与机器学习的比较

2023 Intelligent Methods, Systems, and Applications (IMSA) Pub Date : 2023-07-15 DOI: 10.1109/IMSA58542.2023.10217437

Ahmed Mostafa Abd El-Aal El-Kady, Mohamed Mostafa, Heba Hamdy Ali Hussien, Farid Ali Moussa

{"title":"Comparative Analysis: Deep vs. Machine Learning for Early DFU Detection in Medical Imaging","authors":"Ahmed Mostafa Abd El-Aal El-Kady, Mohamed Mostafa, Heba Hamdy Ali Hussien, Farid Ali Moussa","doi":"10.1109/IMSA58542.2023.10217437","DOIUrl":"https://doi.org/10.1109/IMSA58542.2023.10217437","url":null,"abstract":"Diabetes Mellitus (DM) is a metabolic disorder characterized by aberrant insulin secretion and function, resulting in elevated blood glucose levels and chronic damage to organs. Diabetic Foot Ulcers (DFU) are a significant complication of DM, frequently leading to lower limb amputation if not effectively managed. DFU imposes a substantial burden on patients, families, and healthcare systems, particularly in developing nations where treatment expenses can be overwhelming. Leveraging machine learning and deep learning techniques allows for accurate identification of foot ulcers in diabetic individuals, facilitating early detection and prompt treatment, consequently mitigating the risk of complications and improving the overall quality of life for DM patients. The study focuses on utilizing deep learning and machine learning models to classify diabetic foot ulcers. The results reveal that the RESNET18 model outperforms the SVM models, achieving an accuracy of 97.9%. The study suggests that deep learning models, notably the RESNET18, are more suitable for identifying diabetic foot ulcers.","PeriodicalId":110239,"journal":{"name":"2023 Intelligent Methods, Systems, and Applications (IMSA)","volume":"215 1","pages":"440-445"},"PeriodicalIF":0.0,"publicationDate":"2023-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139359187","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

Advanced Techniques for Business Process Automation: Insights and Challenges 业务流程自动化的高级技术:洞察与挑战

2023 Intelligent Methods, Systems, and Applications (IMSA) Pub Date : 2023-07-15 DOI: 10.1109/IMSA58542.2023.10217503

Mahmoud B. M. Abdelwahab, Iman M. A. Helal

{"title":"Advanced Techniques for Business Process Automation: Insights and Challenges","authors":"Mahmoud B. M. Abdelwahab, Iman M. A. Helal","doi":"10.1109/IMSA58542.2023.10217503","DOIUrl":"https://doi.org/10.1109/IMSA58542.2023.10217503","url":null,"abstract":"An integral part of business process automation is how to select and prioritize candidate processes for automation. This becomes an integral part of process automation in rapidly changing business environments. In recent years, advanced techniques such as machine learning and artificial intelligence (AI) techniques are used for business process modeling and execution. They have gained significant traction, however, there is still a need for comprehensive research on how to most effectively utilize these technologies for process prioritization and automation.In this paper, we provide a comprehensive analysis to ascertain the priority order for process automation. We examine the existing approaches and models that help in process prioritization and assess their strengths and limitations. This study can assist researchers, practitioners, and policymakers to gain insights in selecting the most suitable model based on their business needs. This led to opening new research directions such as incorporating additional criteria and exploring advanced machine learning and AI techniques that can further enhance process automation.","PeriodicalId":110239,"journal":{"name":"2023 Intelligent Methods, Systems, and Applications (IMSA)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133589656","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

Intellibot: A Personalized Behavioral Analysis Chatbot Framework Powered by GPT-3 智能机器人:基于GPT-3的个性化行为分析聊天机器人框架

2023 Intelligent Methods, Systems, and Applications (IMSA) Pub Date : 2023-07-15 DOI: 10.1109/IMSA58542.2023.10217349

Mayar Elshentenawy, Merna Ahmed, Mariam Elalfy, Ahmed Bakr, Mahmoud Heidar, Eslam Amer

{"title":"Intellibot: A Personalized Behavioral Analysis Chatbot Framework Powered by GPT-3","authors":"Mayar Elshentenawy, Merna Ahmed, Mariam Elalfy, Ahmed Bakr, Mahmoud Heidar, Eslam Amer","doi":"10.1109/IMSA58542.2023.10217349","DOIUrl":"https://doi.org/10.1109/IMSA58542.2023.10217349","url":null,"abstract":"This paper is focused on helping individuals with autism, paranoid personality disorder (PPD), and other mental illnesses practice and improve their communication skills by offering them a friendly, intelligent, and comfortable environment in them to express their needs and overcome their daily communication struggles by practicing. The research aims to construct a personalized Chatbot based on GPT-3 technology to provide professional help to individuals with psychological issues. We proposed implementing an advanced system that chats with the user, detects their emotion, and replies accordingly; it also sees negative thoughts during user sessions and automatically terminates the session while referring the individual to a professional psychiatrist if needed. The paper discusses the whole process of developing the Chatbot from the preprocessing steps for the training data to an overview of GPT-3 and its capabilities. Our top priority is to guarantee the safety and well-being of our users; therefore, the paper addresses the challenges faced during the development of the Chatbot, including the unintentional encouragement of negative thoughts and how we overcame these challenges by implementing proactive measures. Additionally, the paper describes text classification using RoBERTa, voice classification using the \"asapp/sew-d-base-plus-400k-ft-ls100h\" model, and a Hidden Markov Model to analyze user emotions and provide appropriate responses. Ultimately, the proposed Chatbot aims to create a friendly and comfortable environment for users while offering professional support, enabling fulfilling connections, and improving their quality of life.","PeriodicalId":110239,"journal":{"name":"2023 Intelligent Methods, Systems, and Applications (IMSA)","volume":"213 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134605545","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: 2

Prediction of Dental Fluorosis Infection based on Particle Optimized Scored KNN Approach 基于粒子优化评分KNN方法的氟斑牙感染预测

2023 Intelligent Methods, Systems, and Applications (IMSA) Pub Date : 2023-07-15 DOI: 10.1109/IMSA58542.2023.10217416

Reem Kadry Montasser, Osama Ismael, Moataz El-Kholy

{"title":"Prediction of Dental Fluorosis Infection based on Particle Optimized Scored KNN Approach","authors":"Reem Kadry Montasser, Osama Ismael, Moataz El-Kholy","doi":"10.1109/IMSA58542.2023.10217416","DOIUrl":"https://doi.org/10.1109/IMSA58542.2023.10217416","url":null,"abstract":"Due to its simplicity of usage across a variety of applications, the K-Nearest Neighbor algorithm is usually utilized as a classification approach. The K-Nearest Neighbor algorithm's accuracy is greatly impacted by the occurrence of multidimensional and outlier data. This research uses a novel hybrid technique known as Particle Optimized Scored K-Nearest Neighbor (POSKNN) to build a model to predict the emergence of dental fluorosis. The proposed novel approach is implemented in two phases: the first phase helps in the resolution of multidimensional data by performing selection of feature using the Modified Particle Swarm Optimization algorithm, and the second phase helps in the resolution of the presence of outliers by making use of the results of the first phase and applying the newly proposed scored KNN technique to them. The suggested approach was tested using a real-world dataset acquired from three dentistry clinics in Egypt's El Baharia Oasis, which has 56 attributes, two classes, and 328 records. 10-fold cross validation was implemented to the model. The experimental evaluation was divided into two parts; evaluation for modified particle swarm optimization, evaluation for scored K nearest neighbor, and the hybrid particle optimized scored K nearest neighbor. The experiment’s results demonstrated that the suggested approach outperformed the traditional KNN and the modified KNN. POSKNN achieved an accuracy of 94.5% when K value is 11.","PeriodicalId":110239,"journal":{"name":"2023 Intelligent Methods, Systems, and Applications (IMSA)","volume":"57 7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131532923","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