Pub Date : 2023-03-18DOI: 10.5121/csit.2023.130512
Sibo Tao, Yu Sun
The abstract describes a research project on the importance of college decision-making for high school students, and how college reviews and reflections can help students make informed decisions. The project focuses on developing an online platform that allows students to view reviews and reflections of former and current college students, covering not only academics, but also other aspects of college life such as culture, geographical location, campus, and tuition. The project includes two experiments, one on the accuracy of a sentiment analysis model and one on the user experience of the software frontend design. The results show that the sentiment analysis model is able to accurately predict positive and negative sentiment comments, but struggles with neutral comments due to data imbalance. The user experience experiment identifies several areas for improvement in the app's UI design. Overall, the research project seeks to provide high school students with a valuable resource for making informed college decisions.
{"title":"An Advantageous and user-friendly Mobile Program to benefit Students in Seeking their Suitable Colleges through the use of Web Scraping, Machine Learning, and Frontend Design","authors":"Sibo Tao, Yu Sun","doi":"10.5121/csit.2023.130512","DOIUrl":"https://doi.org/10.5121/csit.2023.130512","url":null,"abstract":"The abstract describes a research project on the importance of college decision-making for high school students, and how college reviews and reflections can help students make informed decisions. The project focuses on developing an online platform that allows students to view reviews and reflections of former and current college students, covering not only academics, but also other aspects of college life such as culture, geographical location, campus, and tuition. The project includes two experiments, one on the accuracy of a sentiment analysis model and one on the user experience of the software frontend design. The results show that the sentiment analysis model is able to accurately predict positive and negative sentiment comments, but struggles with neutral comments due to data imbalance. The user experience experiment identifies several areas for improvement in the app's UI design. Overall, the research project seeks to provide high school students with a valuable resource for making informed college decisions.","PeriodicalId":261978,"journal":{"name":"Computer Science, Engineering and Applications","volume":"11 5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124616174","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}
Pub Date : 2023-03-18DOI: 10.5121/csit.2023.130502
Harsha Vijayakumar
Artificial Intelligence (AI) has been significant technology of the 21st century. This technology is changing every aspect of modern enterprise technology tooling, from strategies to selecting and implementing to adopting digital AI transformation. The rapid development of Artificial Intelligence has prompted many changes in the field of Information Technology (IT) Service Operations. IT Service Operations are driven by AI, i.e., AIServiceOps. AI has empowered new vitality and addressed many challenges in IT Service Operations. However, there is a literature gap on the Business Value Impact of Artificial intelligence (AI) Powered IT Service Operations. It can help IT build optimized business resilience by creating value in complex and everchanging environments as product organizations move faster than IT can handle. So, this research paper examines how AIServiceOps creates business value and sustainability, basically how AIServiceOps makes the IT staff liberation from a low-level, repetitive workout and traditional IT practices for a continuously optimized process. One of the research objectives is to compare Traditional IT Service Operations with AIServiceOPs. This paper provides the basis for how enterprises can evaluate AIServiceOps and consider it a digital transformation tool.
{"title":"Business Value Impact of AI-Powered Service Operations (AIServiceOps)","authors":"Harsha Vijayakumar","doi":"10.5121/csit.2023.130502","DOIUrl":"https://doi.org/10.5121/csit.2023.130502","url":null,"abstract":"Artificial Intelligence (AI) has been significant technology of the 21st century. This technology is changing every aspect of modern enterprise technology tooling, from strategies to selecting and implementing to adopting digital AI transformation. The rapid development of Artificial Intelligence has prompted many changes in the field of Information Technology (IT) Service Operations. IT Service Operations are driven by AI, i.e., AIServiceOps. AI has empowered new vitality and addressed many challenges in IT Service Operations. However, there is a literature gap on the Business Value Impact of Artificial intelligence (AI) Powered IT Service Operations. It can help IT build optimized business resilience by creating value in complex and everchanging environments as product organizations move faster than IT can handle. So, this research paper examines how AIServiceOps creates business value and sustainability, basically how AIServiceOps makes the IT staff liberation from a low-level, repetitive workout and traditional IT practices for a continuously optimized process. One of the research objectives is to compare Traditional IT Service Operations with AIServiceOPs. This paper provides the basis for how enterprises can evaluate AIServiceOps and consider it a digital transformation tool.","PeriodicalId":261978,"journal":{"name":"Computer Science, Engineering and Applications","volume":"198 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123085122","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}
Pub Date : 2023-03-18DOI: 10.5121/csit.2023.130514
Angelina Zhao, Jonathan Sahagun
In the United States, approximately 1 out of every 44 infants born fall under the autism spectrum, leading them through a life of hardship in the future [7]. Their parents or guardians must pay extra attention to them, as they are not the best at communication and voicing their opinions. As they grow up, their education can fall behind as they struggle in school. Our program allows students to stay on task since a teacher or an adult is always watching over them and guiding them into the right direction. Developed using Python, Thunkable, and Firebase, this program includes 3 major components. The UI component is responsible for the various interactive buttons and boxes [8]. The recording component does the bulk of the job by sending off the data gathered on the student’s movements down to the third component, the database which stores all of their information under each individual user ID.
{"title":"A Perceptive Program to Assist Remote Learning for Students with Learning Disabilities using Screen and Bluetooth Output Tracking","authors":"Angelina Zhao, Jonathan Sahagun","doi":"10.5121/csit.2023.130514","DOIUrl":"https://doi.org/10.5121/csit.2023.130514","url":null,"abstract":"In the United States, approximately 1 out of every 44 infants born fall under the autism spectrum, leading them through a life of hardship in the future [7]. Their parents or guardians must pay extra attention to them, as they are not the best at communication and voicing their opinions. As they grow up, their education can fall behind as they struggle in school. Our program allows students to stay on task since a teacher or an adult is always watching over them and guiding them into the right direction. Developed using Python, Thunkable, and Firebase, this program includes 3 major components. The UI component is responsible for the various interactive buttons and boxes [8]. The recording component does the bulk of the job by sending off the data gathered on the student’s movements down to the third component, the database which stores all of their information under each individual user ID.","PeriodicalId":261978,"journal":{"name":"Computer Science, Engineering and Applications","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115199736","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}
Pub Date : 2023-03-18DOI: 10.5121/csit.2023.130513
V. Ryzhov
Positioning problem can be solved with several approaches in 5G. This paper introduces RT (Ray Tracing) technique for small-cell Outdoor positioning and tracking for systems with distributed architecture with multipath processing gain. Proposed approach exploits highresolution angular spectrum estimation and known radio propagation environment. It solves positioning problem robustly even in NLOS cases via CoMP (Cooperative Multi Point) reception and joint processing at cloud CPU. The aim of this paper is to disclose proposed algorithm for NR and compare it to GNSS measurements.
在5G中，定位问题可以通过几种方法解决。本文介绍了一种基于多径处理增益的分布式系统小单元室外定位跟踪技术。该方法利用了高分辨率角频谱估计和已知的无线电传播环境。通过CoMP (Cooperative Multi Point)接收和云CPU的联合处理，即使在NLOS情况下也能鲁棒地解决定位问题。本文的目的是公开提出的NR算法，并将其与GNSS测量结果进行比较。
{"title":"Robust Outdoor Positioning via Ray Tracing","authors":"V. Ryzhov","doi":"10.5121/csit.2023.130513","DOIUrl":"https://doi.org/10.5121/csit.2023.130513","url":null,"abstract":"Positioning problem can be solved with several approaches in 5G. This paper introduces RT (Ray Tracing) technique for small-cell Outdoor positioning and tracking for systems with distributed architecture with multipath processing gain. Proposed approach exploits highresolution angular spectrum estimation and known radio propagation environment. It solves positioning problem robustly even in NLOS cases via CoMP (Cooperative Multi Point) reception and joint processing at cloud CPU. The aim of this paper is to disclose proposed algorithm for NR and compare it to GNSS measurements.","PeriodicalId":261978,"journal":{"name":"Computer Science, Engineering and Applications","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129868502","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}
Pub Date : 2023-03-18DOI: 10.5121/csit.2023.130509
Junhong Duan, Yujia Zhang
In my freshman year, I joined the school’s football team. However, the application they used at the time was incredibly confusing and difficult to navigate. The scheduling system that is currently in place has much room for improvement. This paper covers the development of an application that implements a new scheduling system that is hopefully easier for people to manage. To test the effectiveness of the application at creating a better user experience, an experiment was performed in which ten participants were gathered to test the features of the application, then complete a Google Forms survey that asked the participants to rate the functionality of the application and the convenience of the application on a scale from one to ten [1][2]. The results indicated that the newly developed application would be a suitable replacement for the current school sports application, as many of the participants stated that the application both functioned properly and was very intuitive.
{"title":"Tion Sport: A Mobile Application Designed to Improve a School’s Sport Event Scheduling System","authors":"Junhong Duan, Yujia Zhang","doi":"10.5121/csit.2023.130509","DOIUrl":"https://doi.org/10.5121/csit.2023.130509","url":null,"abstract":"In my freshman year, I joined the school’s football team. However, the application they used at the time was incredibly confusing and difficult to navigate. The scheduling system that is currently in place has much room for improvement. This paper covers the development of an application that implements a new scheduling system that is hopefully easier for people to manage. To test the effectiveness of the application at creating a better user experience, an experiment was performed in which ten participants were gathered to test the features of the application, then complete a Google Forms survey that asked the participants to rate the functionality of the application and the convenience of the application on a scale from one to ten [1][2]. The results indicated that the newly developed application would be a suitable replacement for the current school sports application, as many of the participants stated that the application both functioned properly and was very intuitive.","PeriodicalId":261978,"journal":{"name":"Computer Science, Engineering and Applications","volume":"2128 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129974453","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}
Pub Date : 2023-03-18DOI: 10.5121/csit.2023.130505
Yuanyuan Ding, Shuyu Wang
In recent years, dance has become a popular entertainment for many people and also an occupation. As a dancer, sometimes it is hard to check how close your cover is vs. the choreographer's because our eyes are not always accurate when we are judging dynamic movement of people, so can artificial intelligence help us to do the work? This paper develops an application which utilizes artificial intelligence, and data analysis skills to develop an application which works on dance scoring [4]. In the application, users can upload two videos, one is their own cover while another one is the original choreography. Then, the application will use MediaPipe to catch the angles of dancers’ bodies in frames then store them in a data abstraction [5]. After all data are collected, the application will use clustering to line up the frames and angles information that are stored. The steps above will be applied to both videos. Next, the application will use an algorithm to compare two videos’ data and calculate a percentage of error of the covering video to the original choreograph and report a grade to the user. We applied our application to users who want to check how similar their covering dances are compared to the original choreographs in order to improve their covering quality [6]. The results show that when users are improving the quality of their covers, they improve their skills of focusing and optimizing details in dance.
{"title":"AIDanceFriend: An Intelligent Mobile Application to Automate the Dance Rating using Artificial Intelligence and Computer Vision","authors":"Yuanyuan Ding, Shuyu Wang","doi":"10.5121/csit.2023.130505","DOIUrl":"https://doi.org/10.5121/csit.2023.130505","url":null,"abstract":"In recent years, dance has become a popular entertainment for many people and also an occupation. As a dancer, sometimes it is hard to check how close your cover is vs. the choreographer's because our eyes are not always accurate when we are judging dynamic movement of people, so can artificial intelligence help us to do the work? This paper develops an application which utilizes artificial intelligence, and data analysis skills to develop an application which works on dance scoring [4]. In the application, users can upload two videos, one is their own cover while another one is the original choreography. Then, the application will use MediaPipe to catch the angles of dancers’ bodies in frames then store them in a data abstraction [5]. After all data are collected, the application will use clustering to line up the frames and angles information that are stored. The steps above will be applied to both videos. Next, the application will use an algorithm to compare two videos’ data and calculate a percentage of error of the covering video to the original choreograph and report a grade to the user. We applied our application to users who want to check how similar their covering dances are compared to the original choreographs in order to improve their covering quality [6]. The results show that when users are improving the quality of their covers, they improve their skills of focusing and optimizing details in dance.","PeriodicalId":261978,"journal":{"name":"Computer Science, Engineering and Applications","volume":"143 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127290269","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}
Pub Date : 2023-03-18DOI: 10.5121/csit.2023.130519
Crystal Chong, Ang Li
An issue that is prevalent in today’s society is the need for new music to be generated. More people are uploading videos and other forms of content to the internet through social media, and videos can often be enhanced by adding music to them [6]. However, creating music can be a time-consuming and expensive process. Therefore, an application was created that can generate music using emotions as inputs for the music generation model. To test how well the method of music generation through sentimental analysis works, an experiment was conducted that tests how accurately a sample of participants believe that the generated music was on a scale from one to ten [7]. According to the results of the experiment, the application appears to do fairly well at generating music that accurately represents the sentiment that was intended in the inputted message. A survey was also conducted to test user satisfaction when working with the application to generate music. The feedback from the participants indicated that they were generally satisfied with how well the generated music matched their intent in the inputted message, and they also seemed to be very satisfied with how convenient the application was to use and how intuitive the user interface was [8]. However, as the ratings for convenience were much higher than the ones regarding the effectiveness of the music generation itself, this may indicate that the application still has room for improvement when it comes to recognizing the sentiment of the inputted message.
{"title":"Emotional Music Generation: An Analysis of Effectiveness and user Satisfaction by using Python and Dart","authors":"Crystal Chong, Ang Li","doi":"10.5121/csit.2023.130519","DOIUrl":"https://doi.org/10.5121/csit.2023.130519","url":null,"abstract":"An issue that is prevalent in today’s society is the need for new music to be generated. More people are uploading videos and other forms of content to the internet through social media, and videos can often be enhanced by adding music to them [6]. However, creating music can be a time-consuming and expensive process. Therefore, an application was created that can generate music using emotions as inputs for the music generation model. To test how well the method of music generation through sentimental analysis works, an experiment was conducted that tests how accurately a sample of participants believe that the generated music was on a scale from one to ten [7]. According to the results of the experiment, the application appears to do fairly well at generating music that accurately represents the sentiment that was intended in the inputted message. A survey was also conducted to test user satisfaction when working with the application to generate music. The feedback from the participants indicated that they were generally satisfied with how well the generated music matched their intent in the inputted message, and they also seemed to be very satisfied with how convenient the application was to use and how intuitive the user interface was [8]. However, as the ratings for convenience were much higher than the ones regarding the effectiveness of the music generation itself, this may indicate that the application still has room for improvement when it comes to recognizing the sentiment of the inputted message.","PeriodicalId":261978,"journal":{"name":"Computer Science, Engineering and Applications","volume":"199 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121714372","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}
Pub Date : 2023-03-18DOI: 10.5121/csit.2023.130501
Jay Pang, Marisabel Chang
The aim of this paper is to apply computer techniques to assist high school students' essay writing. A python program named Fun Writer is developed to assist users in paraphrasing, summarizing, and keywording. We applied it to real text sentences and paragraphs and conducted a qualitative evaluation of the approach. The results show that Fun Writer can automatically provide users with different versions of sentence paraphrases, Text or paragraph summaries, and keyword retrieval, thus being flexible to the user’s needs. The program will be a website where the user can upload his own input text and freely select to either paraphrase, summarize, or extract keywords.
{"title":"Fun Writer: A Context-Based Intelligent Writing Platform to Assist and Motivate Writing Activities using Artificial Intelligence and Natural Language Processing","authors":"Jay Pang, Marisabel Chang","doi":"10.5121/csit.2023.130501","DOIUrl":"https://doi.org/10.5121/csit.2023.130501","url":null,"abstract":"The aim of this paper is to apply computer techniques to assist high school students' essay writing. A python program named Fun Writer is developed to assist users in paraphrasing, summarizing, and keywording. We applied it to real text sentences and paragraphs and conducted a qualitative evaluation of the approach. The results show that Fun Writer can automatically provide users with different versions of sentence paraphrases, Text or paragraph summaries, and keyword retrieval, thus being flexible to the user’s needs. The program will be a website where the user can upload his own input text and freely select to either paraphrase, summarize, or extract keywords.","PeriodicalId":261978,"journal":{"name":"Computer Science, Engineering and Applications","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121849257","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}
Pub Date : 2023-03-18DOI: 10.5121/csit.2023.130518
Jiuyu Zhang, Sanskar Pokharel
How does Machine Learning fit into the aspect of a highschooler searching for their dream college? It is widely known that being in high school is a stressful for most high school student, and creating something that can help them find the best college is important. Knowing that high school students like to participate in social activity, creating a chatting service that uses machine learning serves the purpose of helping them find their most suitable college without increasing the stress of their already stressful situation . To prove that this method is suitable for the situation, a survey asking 1000 high school students whether they would choose the chat option or traditional fill-out a form method, majority of them preferred the chat way. Based on the results supporting my thesis, I developed an application that will help high school students find their best college that consists of a chatting service that helps students achieve their goal with the help of Machine Learning.
{"title":"Machine Learning and Chatting Services in College Search: A Study on Students' Preferences and Satisfaction","authors":"Jiuyu Zhang, Sanskar Pokharel","doi":"10.5121/csit.2023.130518","DOIUrl":"https://doi.org/10.5121/csit.2023.130518","url":null,"abstract":"How does Machine Learning fit into the aspect of a highschooler searching for their dream college? It is widely known that being in high school is a stressful for most high school student, and creating something that can help them find the best college is important. Knowing that high school students like to participate in social activity, creating a chatting service that uses machine learning serves the purpose of helping them find their most suitable college without increasing the stress of their already stressful situation . To prove that this method is suitable for the situation, a survey asking 1000 high school students whether they would choose the chat option or traditional fill-out a form method, majority of them preferred the chat way. Based on the results supporting my thesis, I developed an application that will help high school students find their best college that consists of a chatting service that helps students achieve their goal with the help of Machine Learning.","PeriodicalId":261978,"journal":{"name":"Computer Science, Engineering and Applications","volume":"201 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127707286","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}
Pub Date : 2023-03-18DOI: 10.5121/csit.2023.130510
Mayar Osama, Mervat Abu Elkheir
Knowledge Graphs (KGs) are a type of knowledge representation that gained a lot of attention due to their ability to store information in a structured format. This structure representation makes KGs naturally suited for search engines and NLP tasks like question-answering (QA) and task-oriented systems; however, KGs are hard to construct. While QA datasets are more available and easier to construct, they lack structural representation. This availability of QA datasets made them a rich resource for machine learning models, but these models benefit from the implicit structure in such datasets. We propose a framework to make this structure more pronounced and extract KG from QA datasets in an end-to-end manner, allowing the system to learn new knowledge in incremental learning with a human-in-the-loop (HITL) when needed. We test our framework using the SQuAD dataset and our incremental learning approach with two datasets, YAGO3-10 and FB15K237, both of which show promising results.
{"title":"Can Incremental Learning help with KG Completion?","authors":"Mayar Osama, Mervat Abu Elkheir","doi":"10.5121/csit.2023.130510","DOIUrl":"https://doi.org/10.5121/csit.2023.130510","url":null,"abstract":"Knowledge Graphs (KGs) are a type of knowledge representation that gained a lot of attention due to their ability to store information in a structured format. This structure representation makes KGs naturally suited for search engines and NLP tasks like question-answering (QA) and task-oriented systems; however, KGs are hard to construct. While QA datasets are more available and easier to construct, they lack structural representation. This availability of QA datasets made them a rich resource for machine learning models, but these models benefit from the implicit structure in such datasets. We propose a framework to make this structure more pronounced and extract KG from QA datasets in an end-to-end manner, allowing the system to learn new knowledge in incremental learning with a human-in-the-loop (HITL) when needed. We test our framework using the SQuAD dataset and our incremental learning approach with two datasets, YAGO3-10 and FB15K237, both of which show promising results.","PeriodicalId":261978,"journal":{"name":"Computer Science, Engineering and Applications","volume":"2009 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125622980","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}
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