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Assessing the Effectiveness of Textual Recommendations in KoopaML 评估 KoopaML 中文本推荐的有效性
International Journal on Semantic Web and Information Systems Pub Date : 2024-03-19 DOI: 10.4018/ijswis.340727
Pablo Antúnez-Muiños, Pablo Pérez-Sánchez, Andrea Vázquez-Ingelmo, F. García-Peñalvo, A. Sánchez-Puente, Víctor Vicente-Palacios, Alicia García-Holgado, P. Dorado-Díaz, Jesús Sampedro-Gómez, Ignacio Cruz-González, P. L. Sánchez
{"title":"Assessing the Effectiveness of Textual Recommendations in KoopaML","authors":"Pablo Antúnez-Muiños, Pablo Pérez-Sánchez, Andrea Vázquez-Ingelmo, F. García-Peñalvo, A. Sánchez-Puente, Víctor Vicente-Palacios, Alicia García-Holgado, P. Dorado-Díaz, Jesús Sampedro-Gómez, Ignacio Cruz-González, P. L. Sánchez","doi":"10.4018/ijswis.340727","DOIUrl":"https://doi.org/10.4018/ijswis.340727","url":null,"abstract":"Artificial intelligence (AI) integration, notably in healthcare, has been significant, yet effective implementation in critical areas requires expertise. KoopaML, a previously developed visual platform, aims at bridging this gap, enabling users with limited AI knowledge to build ML pipelines. Its core is a heuristic-based ML task recommender, offering guidance and contextual explanations. The authors compared the use of KoopaML with two non-expert groups: one with the recommender system enabled and the other without. Results showed KoopaML's intuitiveness benefits all but emphasized that textual guidance doesn't substitute for fundamental ML understanding. This underscores the need for educational components in such tools, especially in critical fields like healthcare. The paper suggests future KoopaML enhancements include educational modules, making ML accessible, and ensuring users develop a solid AI foundation. This is crucial for quality outcomes in sectors like healthcare, leveraging AI's potential through enhanced non-expert user capability.","PeriodicalId":508238,"journal":{"name":"International Journal on Semantic Web and Information Systems","volume":"58 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140228229","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
A Model for Predicting Physical Health of College Students Based on Semantic Web and Deep Learning Under Cloud Edge Collaborative Architecture 云边缘协作架构下基于语义网和深度学习的大学生体质健康预测模型
International Journal on Semantic Web and Information Systems Pub Date : 2024-03-12 DOI: 10.4018/ijswis.340379
Yu Wang, Zhiyi Zhang, Peng Tang, Shiyao Bian
{"title":"A Model for Predicting Physical Health of College Students Based on Semantic Web and Deep Learning Under Cloud Edge Collaborative Architecture","authors":"Yu Wang, Zhiyi Zhang, Peng Tang, Shiyao Bian","doi":"10.4018/ijswis.340379","DOIUrl":"https://doi.org/10.4018/ijswis.340379","url":null,"abstract":"A model for predicting physical health of college students based on semantic web and deep learning under cloud edge collaborative architecture is proposed to address the issue of most physical health prediction models being unable to fully describe the characteristics of sports performance changes and having large prediction errors. Firstly, the authors design a measurement data analysis system based on cloud edge collaboration architecture to improve data analysis efficiency. Then, they preprocess the data on the edge side, such as missing samples, and extract data features using an equal dimensional dynamic GOM model. Finally, they deploy the RBFNN-SSA model in the cloud center, input the characteristics of each indicator into the model for predictive analysis, and obtain the physical health status of college students. Based on the physical health test data of Hohai University from 2018 to 2021, an experimental analysis was conducted. The results showed that all three intervention measures had significant effects on maintaining and improving the physical health level of college students.","PeriodicalId":508238,"journal":{"name":"International Journal on Semantic Web and Information Systems","volume":"75 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140249645","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
Affective Prompt-Tuning-Based Language Model for Semantic-Based Emotional Text Generation 基于情感提示调谐的语言模型，用于基于语义的情感文本生成
International Journal on Semantic Web and Information Systems Pub Date : 2024-03-07 DOI: 10.4018/ijswis.339187
Zhaodong Gu, Kejing He
{"title":"Affective Prompt-Tuning-Based Language Model for Semantic-Based Emotional Text Generation","authors":"Zhaodong Gu, Kejing He","doi":"10.4018/ijswis.339187","DOIUrl":"https://doi.org/10.4018/ijswis.339187","url":null,"abstract":"The large language models based on transformers have shown strong text generation ability. However, due to the need for significant computing resources, little work has been done to generate emotional text using language models such as GPT-2. To address this issue, the authors proposed an affective prompt-tuning-based language model (APT-LM) equipped with an affective decoding (AD) method, aiming to enhance emotional text generation with limited computing resources. In detail, the proposed model incorporates the emotional attributes into the soft prompt by using the NRC emotion intensity lexicon and updates the additional parameters while freezing the language model. Then, it steers the generation toward a given emotion by calculating the cosine distance between the affective soft prompt and the candidate tokens generated by the language model. Experimental results show that the proposed APT-LM model significantly improves emotional text generation and achieves competitive performance on sentence fluency compared to baseline models across automatic evaluation and human evaluation.","PeriodicalId":508238,"journal":{"name":"International Journal on Semantic Web and Information Systems","volume":"30 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140259549","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
Stability Analysis of EPC Consortium Cooperation Based on Evolutionary Game 基于进化博弈的 EPC 联盟合作稳定性分析
International Journal on Semantic Web and Information Systems Pub Date : 2024-03-07 DOI: 10.4018/ijswis.339001
Judan Hu, Yu Yao, Yuyang Gao
{"title":"Stability Analysis of EPC Consortium Cooperation Based on Evolutionary Game","authors":"Judan Hu, Yu Yao, Yuyang Gao","doi":"10.4018/ijswis.339001","DOIUrl":"https://doi.org/10.4018/ijswis.339001","url":null,"abstract":"Consortium contracting is a contracting model that China encourages and advocates. Due to the interest drive, members within the consortium are very prone to negative cooperation and midway withdrawal, which hinders the healthy development of the consortium. Therefore, this paper constructs a game model of EPC consortium cooperation evolution, analyzes the influence of different reward and punishment mechanisms on the cooperation of consortium members, and applies system dynamics to simulation. The results show that under the static reward and punishment and dynamic reward mechanism, the consortium cooperation is not stable; while under the dynamic punishment mechanism and the dynamic reward and punishment mechanism in which the maximum punishment is greater than the maximum reward, the evolution of consortium cooperation is gradually stable and the behavioral strategies are gradually unified. It also puts forward suggestions for measures conducive to stabilizing cooperation, which provide certain reference value for the internal management of consortium members' cooperation.","PeriodicalId":508238,"journal":{"name":"International Journal on Semantic Web and Information Systems","volume":"4 5","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140260319","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
A Semantic Web-Based Approach for Bat Trajectory Reconstruction With Human Keypoint Information 利用人类关键点信息重建蝙蝠轨迹的语义网方法
International Journal on Semantic Web and Information Systems Pub Date : 2024-03-06 DOI: 10.4018/ijswis.338999
Zechen Jin, Yida Zheng, Jun Liu, Yang Yu
{"title":"A Semantic Web-Based Approach for Bat Trajectory Reconstruction With Human Keypoint Information","authors":"Zechen Jin, Yida Zheng, Jun Liu, Yang Yu","doi":"10.4018/ijswis.338999","DOIUrl":"https://doi.org/10.4018/ijswis.338999","url":null,"abstract":"Restoring the trajectory of a bat from a table tennis match video is critical in analyzing a table tennis technique and conducting statistical analysis. However, directly bat location detection in each frame is challenging due to changing shapes caused by varying movement directions and speeds, leading to ambiguity. This paper develops a novel two-stage method. The first stage utilizes YOLO for bat detection in each frame, followed by filtering out erroneous candidate boxes. In the second stage, the authors use a temporal prediction model that integrating human keypoint information and interpolation to reconstruct a complete bat trajectory with minimal errors. The method's effectiveness and performance are evaluated on our video datasets. The evaluation results demonstrate that the proposed method outperforms traditional methods on precision performance metrics. The error screening algorithm improves precision score to nearly 1. In addition, the method has the recall score 22.3% higher than YOLO 's and also 1.4% higher than that of YOLO with cubic spline interpolation.","PeriodicalId":508238,"journal":{"name":"International Journal on Semantic Web and Information Systems","volume":"54 6","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140077942","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
Web-Semantic-Driven Machine Learning and Blockchain for Transformative Change in the Future of Physical Education 网络语义驱动的机器学习和区块链促进体育教育未来的转型变革
International Journal on Semantic Web and Information Systems Pub Date : 2024-02-14 DOI: 10.4018/ijswis.337961
Wang Jun, Muhammad Shahid Iqbal, Rashid Abbasi, Marwan Omar, Huiqin Chu
{"title":"Web-Semantic-Driven Machine Learning and Blockchain for Transformative Change in the Future of Physical Education","authors":"Wang Jun, Muhammad Shahid Iqbal, Rashid Abbasi, Marwan Omar, Huiqin Chu","doi":"10.4018/ijswis.337961","DOIUrl":"https://doi.org/10.4018/ijswis.337961","url":null,"abstract":"Machine learning is playing an increasingly important role in education. This article examines its potential to bring about transformative change in this field. By using machine learning algorithms, physical education teachers can gather and analyze data on student performance and behavior. This enables them to create personalized learning experiences that cater to the unique needs of each student. Machine learning can also track and assess student progress, providing educators with valuable insights into the effectiveness of their teaching strategies. Furthermore, it can optimize the design of physical education curricula and assessments, making them more efficient and effective. Additionally, machine learning offers a more objective and accurate approach to evaluating and grading students. This paper discusses the challenges and opportunities associated with integrating machine learning into physical education, including ethical considerations and potential limitations.","PeriodicalId":508238,"journal":{"name":"International Journal on Semantic Web and Information Systems","volume":"62 5","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139779068","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
Web-Semantic-Driven Machine Learning and Blockchain for Transformative Change in the Future of Physical Education 网络语义驱动的机器学习和区块链促进体育教育未来的转型变革
International Journal on Semantic Web and Information Systems Pub Date : 2024-02-14 DOI: 10.4018/ijswis.337961
Wang Jun, Muhammad Shahid Iqbal, Rashid Abbasi, Marwan Omar, Huiqin Chu
{"title":"Web-Semantic-Driven Machine Learning and Blockchain for Transformative Change in the Future of Physical Education","authors":"Wang Jun, Muhammad Shahid Iqbal, Rashid Abbasi, Marwan Omar, Huiqin Chu","doi":"10.4018/ijswis.337961","DOIUrl":"https://doi.org/10.4018/ijswis.337961","url":null,"abstract":"Machine learning is playing an increasingly important role in education. This article examines its potential to bring about transformative change in this field. By using machine learning algorithms, physical education teachers can gather and analyze data on student performance and behavior. This enables them to create personalized learning experiences that cater to the unique needs of each student. Machine learning can also track and assess student progress, providing educators with valuable insights into the effectiveness of their teaching strategies. Furthermore, it can optimize the design of physical education curricula and assessments, making them more efficient and effective. Additionally, machine learning offers a more objective and accurate approach to evaluating and grading students. This paper discusses the challenges and opportunities associated with integrating machine learning into physical education, including ethical considerations and potential limitations.","PeriodicalId":508238,"journal":{"name":"International Journal on Semantic Web and Information Systems","volume":"692 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139839173","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
Web Semantic-Based Robust Graph Contrastive Learning for Recommendation via Invariant Learning 基于网络语义的鲁棒图对比学习，通过不变性学习进行推荐
International Journal on Semantic Web and Information Systems Pub Date : 2024-02-14 DOI: 10.4018/ijswis.337962
Wengui Dai, Yujun Wang
{"title":"Web Semantic-Based Robust Graph Contrastive Learning for Recommendation via Invariant Learning","authors":"Wengui Dai, Yujun Wang","doi":"10.4018/ijswis.337962","DOIUrl":"https://doi.org/10.4018/ijswis.337962","url":null,"abstract":"The use of contrastive learning (CL) in recommendation has advanced significantly. Recently, some works use perturbations in the embedding space to obtain enhanced views of nodes. This makes the representation distribution of nodes more even and then improve recommendation effectiveness. In this article, the authors provide an explanation on the role of added noises in the embedding space from the perspective of invariant learning and feature selection. Guided by this thinking, the authors devise a more reasonable method for generating random noises and put forward web semantic based robust graph contrastive learning for recommendation via invariant learning, a novel graph CL-based recommendation model, named RobustGCL. RobustGCL, randomly zeros the values of certain dimensions in the noise vectors at a fixed ratio. In this way, RobustGCL can identify invariant and variant features and then learn invariant and variant representations. Tests on publicly available datasets show that our proposed approach can learn invariant representations and achieve better performance.","PeriodicalId":508238,"journal":{"name":"International Journal on Semantic Web and Information Systems","volume":"63 49","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139778753","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
Web Semantic-Based Robust Graph Contrastive Learning for Recommendation via Invariant Learning 基于网络语义的鲁棒图对比学习，通过不变性学习进行推荐
International Journal on Semantic Web and Information Systems Pub Date : 2024-02-14 DOI: 10.4018/ijswis.337962
Wengui Dai, Yujun Wang
{"title":"Web Semantic-Based Robust Graph Contrastive Learning for Recommendation via Invariant Learning","authors":"Wengui Dai, Yujun Wang","doi":"10.4018/ijswis.337962","DOIUrl":"https://doi.org/10.4018/ijswis.337962","url":null,"abstract":"The use of contrastive learning (CL) in recommendation has advanced significantly. Recently, some works use perturbations in the embedding space to obtain enhanced views of nodes. This makes the representation distribution of nodes more even and then improve recommendation effectiveness. In this article, the authors provide an explanation on the role of added noises in the embedding space from the perspective of invariant learning and feature selection. Guided by this thinking, the authors devise a more reasonable method for generating random noises and put forward web semantic based robust graph contrastive learning for recommendation via invariant learning, a novel graph CL-based recommendation model, named RobustGCL. RobustGCL, randomly zeros the values of certain dimensions in the noise vectors at a fixed ratio. In this way, RobustGCL can identify invariant and variant features and then learn invariant and variant representations. Tests on publicly available datasets show that our proposed approach can learn invariant representations and achieve better performance.","PeriodicalId":508238,"journal":{"name":"International Journal on Semantic Web and Information Systems","volume":"40 7","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139838375","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
Bidirectional Complementary Correlation-Based Multimodal Aspect-Level Sentiment Analysis 基于双向互补相关性的多模态方面情感分析
International Journal on Semantic Web and Information Systems Pub Date : 2024-02-13 DOI: 10.4018/ijswis.337598
Jing Yang, Yujie Xiong
{"title":"Bidirectional Complementary Correlation-Based Multimodal Aspect-Level Sentiment Analysis","authors":"Jing Yang, Yujie Xiong","doi":"10.4018/ijswis.337598","DOIUrl":"https://doi.org/10.4018/ijswis.337598","url":null,"abstract":"Aspect-based sentiment analysis is the key to natural language processing, and it focuses on the polarity of emotions associated with specific text aspects. Traditional models that combine text and visual data tend to ignore the deeper interconnections between patterns. To solve this problem, the authors propose a multimodal sentiment-oriented analysis (BiCCM-ABSA) model based on bidirectional complementary correlation. The model utilizes text-image synergy through a novel cross-modal attention mechanism to align text with image features. With the transformer architecture, it is not only a simple fusion, but also ensures the complex alignment of multi-modal features and gating mechanisms. Experiments were conducted on the Twitter-15 and Twitter-17 datasets, achieving 69.28 accuracy and 67.54% F1 score, respectively. The experimental results demonstrate the advantages of BiCCM-ABSA, the bidirectional approach of the model and the effective cross-modal correlation set a new benchmark in the field of multimodal emotion recognition, providing insights beyond traditional single-modal analysis.","PeriodicalId":508238,"journal":{"name":"International Journal on Semantic Web and Information Systems","volume":"91 6","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139839624","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
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