Expert Systems with Applications最新文献

筛选
英文 中文
Insect identification by combining different neural networks
IF 7.5 1区 计算机科学
Expert Systems with Applications Pub Date : 2025-02-16 DOI: 10.1016/j.eswa.2025.126935
Loris Nanni , Nicola Maritan , Daniel Fusaro , Sheryl Brahnam , Francesco Boscolo Meneguolo , Maria Sgaravatto
{"title":"Insect identification by combining different neural networks","authors":"Loris Nanni ,&nbsp;Nicola Maritan ,&nbsp;Daniel Fusaro ,&nbsp;Sheryl Brahnam ,&nbsp;Francesco Boscolo Meneguolo ,&nbsp;Maria Sgaravatto","doi":"10.1016/j.eswa.2025.126935","DOIUrl":"10.1016/j.eswa.2025.126935","url":null,"abstract":"<div><h3>Background</h3><div>Traditional insect species classification relies on taxonomic experts examining unique physical characteristics of specimens, a time-consuming and error-prone process. Machine learning (ML) offers a promising alternative by identifying subtle morphological and genetic differences computationally. However, most existing approaches classify undescribed species as outliers, which limits their utility for biodiversity monitoring.</div></div><div><h3>Objective</h3><div>This study aims to develop an ML method capable of simultaneously classifying described species and grouping undescribed species by genus, thereby advancing the field of automated insect classification.</div></div><div><h3>Method</h3><div>We propose a novel ensemble approach combining neural networks (convolutional and attention-based) and Support Vector Machines (SVM), with both DNA barcoding and insect images as input data. To optimize the neural networks for diverse data types, we transform one-dimensional feature vectors into matrices using wavelet transforms. Additionally, a transformer-based architecture integrates DNA barcoding and image features for enhanced classification accuracy.</div></div><div><h3>Experimental Results</h3><div>Our method was evaluated on a comprehensive dataset containing paired insect images and DNA barcodes for 1,040 species across four insect orders. The results demonstrate superior performance compared to existing methods in classifying described species and grouping undescribed ones by genus.</div></div><div><h3>Conclusion</h3><div>The proposed approach represents a significant advancement in automated insect classification, addressing both described and undescribed species. This method has the potential to revolutionize global biodiversity monitoring. The MATLAB/PyTorch source code and dataset used are available at <span><span>https://github.com/LorisNanni/Insect-identification</span><svg><path></path></svg></span>.</div></div>","PeriodicalId":50461,"journal":{"name":"Expert Systems with Applications","volume":"273 ","pages":"Article 126935"},"PeriodicalIF":7.5,"publicationDate":"2025-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143428994","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Stockformer: A price–volume factor stock selection model based on wavelet transform and multi-task self-attention networks
IF 7.5 1区 计算机科学
Expert Systems with Applications Pub Date : 2025-02-15 DOI: 10.1016/j.eswa.2025.126803
Bohan Ma , Yushan Xue , Yuan Lu, Jing Chen
{"title":"Stockformer: A price–volume factor stock selection model based on wavelet transform and multi-task self-attention networks","authors":"Bohan Ma ,&nbsp;Yushan Xue ,&nbsp;Yuan Lu,&nbsp;Jing Chen","doi":"10.1016/j.eswa.2025.126803","DOIUrl":"10.1016/j.eswa.2025.126803","url":null,"abstract":"<div><div>As the Chinese stock market continues to evolve and its market structure grows increasingly complex, traditional quantitative trading methods face escalating challenges. Due to policy uncertainty and frequent market fluctuations triggered by sudden economic events, existing models often struggle to predict market dynamics accurately. To address these challenges, this paper introduces “Stockformer,” a price–volume factor stock selection model that integrates wavelet transformation and a multitask self-attention network to enhance responsiveness and predictive accuracy regarding market instabilities. Through discrete wavelet transform, Stockformer decomposes stock returns into high and low frequencies, meticulously capturing long-term market trends and short-term fluctuations, including abrupt events. Moreover, the model incorporates a Dual-Frequency Spatiotemporal Encoder and graph embedding techniques to capture complex temporal and spatial relationships among stocks effectively. Employing a multitask learning strategy, it simultaneously predicts stock returns and directional trends. Experimental results show that Stockformer outperforms existing advanced methods on multiple real stock market datasets. In strategy backtesting, Stockformer consistently demonstrates exceptional stability and reliability across market conditions—whether rising, falling, or fluctuating—particularly maintaining high performance during downturns or volatile periods, indicating high adaptability to market fluctuations. To foster innovation and collaboration in the financial analysis sector, the Stockformer model’s code has been open-sourced and is available on the GitHub repository: <span><span>https://github.com/Eric991005/Multitask-Stockformer</span><svg><path></path></svg></span>.</div></div>","PeriodicalId":50461,"journal":{"name":"Expert Systems with Applications","volume":"273 ","pages":"Article 126803"},"PeriodicalIF":7.5,"publicationDate":"2025-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143428992","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Development and validation of a human-machine interface for unmanned aerial vehicle (UAV) control via hand gesture teleoperation
IF 7.5 1区 计算机科学
Expert Systems with Applications Pub Date : 2025-02-15 DOI: 10.1016/j.eswa.2025.126828
Fevzi Çakmak Bolat , Mustafa Cem Avci
{"title":"Development and validation of a human-machine interface for unmanned aerial vehicle (UAV) control via hand gesture teleoperation","authors":"Fevzi Çakmak Bolat ,&nbsp;Mustafa Cem Avci","doi":"10.1016/j.eswa.2025.126828","DOIUrl":"10.1016/j.eswa.2025.126828","url":null,"abstract":"<div><div>In this research, a drone-style unmanned aerial vehicle is maneuvered using hand gestures through the creation of a specialized glove design. The analytical formulas pertaining to the drone framework developed during the research were derived, leading to the establishment of a mathematical representation. These formulas were implemented in the Matlab &amp; Simulink environment, and simulations of the system based on this mathematical representation were conducted. Next, to carry out verification tests, a unique device was crafted and set up for the drone, enabling real-time data exchange with the glove. A series of distinct signal sets for the glove were examined to confirm the functionality of the system. After confirming the control mechanism, it was seamlessly incorporated into the electronic hardware framework, leveraging the Arduino Uno microcontroller as the focal point. Within the hand gesture apparatus, an innovative circuit was devised, managed by the Atmega328P microcontroller chip. The primary motivation behind this exploration resides in the desire to establish a user interface for UAV operators that is both seamless and unobtrusive, moving beyond the artificial and cumbersome elements tied to traditional control systems. For this purpose, the research aims to empower users to utilize hand gestures—frequently employed in various everyday scenarios—for piloting activities, thus improving user performance and simplicity of use. The findings of this study highlight the parity between the glove apparatus designed for hand gesture manipulation and the conventional joystick-based system, thereby confirming its effectiveness for multiple applications. Furthermore, a one-handed method was embraced for hand gesture control, with the supplementary aim of offering pilot training opportunities for individuals with upper limb impairments.</div></div>","PeriodicalId":50461,"journal":{"name":"Expert Systems with Applications","volume":"273 ","pages":"Article 126828"},"PeriodicalIF":7.5,"publicationDate":"2025-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143428993","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
ODTE—An ensemble of multi-class SVM-based oblique decision trees
IF 7.5 1区 计算机科学
Expert Systems with Applications Pub Date : 2025-02-15 DOI: 10.1016/j.eswa.2025.126833
Ricardo Montañana, José A. Gámez, José M. Puerta
{"title":"ODTE—An ensemble of multi-class SVM-based oblique decision trees","authors":"Ricardo Montañana,&nbsp;José A. Gámez,&nbsp;José M. Puerta","doi":"10.1016/j.eswa.2025.126833","DOIUrl":"10.1016/j.eswa.2025.126833","url":null,"abstract":"<div><div>We propose ODTE, a new ensemble that uses oblique decision trees as base classifiers. Additionally, we introduce STree, the base algorithm for growing oblique decision trees, which leverages support vector machines to define hyperplanes within the decision nodes. We embed a multiclass strategy (one-vs-one or one-vs-rest) at the decision nodes, allowing the model to directly handle non-binary classification tasks without the need to cluster instances into two groups, as is common in other approaches from the literature. In each decision node, only the best-performing model (SVM)—the one that minimizes an impurity measure for the n-ary classification—is retained, even if the learned SVM addresses a binary classification subtask. An extensive experimental study involving 49 datasets and various state-of-the-art algorithms for oblique decision tree ensembles has been conducted. Our results show that ODTE ranks consistently above its competitors, achieving significant performance gains when hyperparameters are carefully tuned. Moreover, the oblique decision trees learned through STree are more compact than those produced by other algorithms evaluated in our experiments.</div></div>","PeriodicalId":50461,"journal":{"name":"Expert Systems with Applications","volume":"273 ","pages":"Article 126833"},"PeriodicalIF":7.5,"publicationDate":"2025-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143429279","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Joint optimization of quality control and maintenance policy for a production system with quality-dependent failures
IF 7.5 1区 计算机科学
Expert Systems with Applications Pub Date : 2025-02-14 DOI: 10.1016/j.eswa.2025.126800
Jingjing Wang , Lingyun Luo , Guoqing Mu , Yingying Ma , Chao Ni
{"title":"Joint optimization of quality control and maintenance policy for a production system with quality-dependent failures","authors":"Jingjing Wang ,&nbsp;Lingyun Luo ,&nbsp;Guoqing Mu ,&nbsp;Yingying Ma ,&nbsp;Chao Ni","doi":"10.1016/j.eswa.2025.126800","DOIUrl":"10.1016/j.eswa.2025.126800","url":null,"abstract":"<div><div>A machine is either subject to hard failure or soft failure, while quality-dependent failure is usually ignored in production systems. However, in practice, non-conforming products generally accelerate the degradation process of production systems. To fill these gaps, this paper formulated an integrated model of the optimal quality control policy and maintenance policies under the quality-dependent failures for production systems. Since the severe degradation of product machines directly impacts the non-conforming rate, effective preventive and opportunistic maintenance actions are necessary. Moreover, the production system can timely be corrected from an out-of-control state to a control state after adopting a minimal repair. An opportunity is created based on the buffer inventory level instead of the machine degradation level, which is different from previous research. The production machine can be opportunistically maintained at the point of maximum inventory. The renewal process is utilized to derive the integrated optimization model, and the collaboration relationship among production, quality control and maintenance management problems is taken into consideration. The system’s total cost rate is minimized by optimizing the preventive maintenance threshold and sampling control coefficients. Numerical examples are given to illustrate the priority of the proposed model and the optimal results are obtained by differential evaluation algorithm, which provides a more meaningful perspective for managers.</div></div>","PeriodicalId":50461,"journal":{"name":"Expert Systems with Applications","volume":"272 ","pages":"Article 126800"},"PeriodicalIF":7.5,"publicationDate":"2025-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143403699","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Inspired by “Focus, Fusion, Collaboration”: A multi-level ensemble network for automatic pneumonia diagnosis from full slice CT images
IF 7.5 1区 计算机科学
Expert Systems with Applications Pub Date : 2025-02-14 DOI: 10.1016/j.eswa.2025.126806
Linna Zhao, Jianqiang Li, Qing Zhao, Xi Xu
{"title":"Inspired by “Focus, Fusion, Collaboration”: A multi-level ensemble network for automatic pneumonia diagnosis from full slice CT images","authors":"Linna Zhao,&nbsp;Jianqiang Li,&nbsp;Qing Zhao,&nbsp;Xi Xu","doi":"10.1016/j.eswa.2025.126806","DOIUrl":"10.1016/j.eswa.2025.126806","url":null,"abstract":"<div><div>Pneumonia is an infectious disease that endangers human health. With advancements in science and technology, deep learning-driven techniques have gained prominence in this field. However, their applicability to clinical practice remains limited because they mostly neglect three key points: focus on local lesion regions, multi-level feature fusion, and sequential collaborative decision-making. In this paper, we present a novel multi-level ensemble network for automatic pneumonia diagnosis from full slice CT images, inspired by the “Focus, Fusion, Collaboration” strategy. Our proposed model involves three modules: the global–local feature extraction module is first designed to fully extract the global structure information and local lesion details; subsequently, the multi-level feature fusion module is responsible for integrating the above-mentioned global and local information; finally, the sequential pneumonia prediction module is utilized to learn the contextual relationship between the adjacent slices, thus generating the final diagnosis results. Building upon mimicking the diagnostic behavior from real-world clinical scenarios, our model enables the integration of multiple types of information (including global structure information, local lesion features, and slice dependencies) and sequential pneumonia diagnosis. Extensive comparative experiments are conducted to verify the feasibility and effectiveness of our proposed method. The experimental results show that our model can obtain an accuracy of 91.4% in a four-class pneumonia diagnosis task, outperforming the other classical works.</div></div>","PeriodicalId":50461,"journal":{"name":"Expert Systems with Applications","volume":"273 ","pages":"Article 126806"},"PeriodicalIF":7.5,"publicationDate":"2025-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143428996","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Human centric VR system development supporting fire emergency evacuation: A novel knowledge-data dual driven approach
IF 7.5 1区 计算机科学
Expert Systems with Applications Pub Date : 2025-02-13 DOI: 10.1016/j.eswa.2025.126895
Jiaxin Ling , Xiaojun Li , Yi Shen , Chao Chen , Zhiguo Yan , Hehua Zhu , Haijiang Li
{"title":"Human centric VR system development supporting fire emergency evacuation: A novel knowledge-data dual driven approach","authors":"Jiaxin Ling ,&nbsp;Xiaojun Li ,&nbsp;Yi Shen ,&nbsp;Chao Chen ,&nbsp;Zhiguo Yan ,&nbsp;Hehua Zhu ,&nbsp;Haijiang Li","doi":"10.1016/j.eswa.2025.126895","DOIUrl":"10.1016/j.eswa.2025.126895","url":null,"abstract":"<div><div>Catastrophic fire accidents happened inside the tunnel have made it evident that human factors, especially misconduct, should be taken into account when it comes to fire emergency evacuation. However, conventional approaches separate fire safety education from evacuation training, failing to account for individual capabilities and behavioral dynamics, resulting in less intuitive and ineffective preparedness. A human-centric and more adaptive training for tunnel fire evacuation which takes both knowledge learning and behavior training into account is in urgent need. Motivated by such need, this study proposes a knowledge-data dual driven (KD3) framework, to seamlessly combine tunnel fire knowledge transfer and evacuation training into a unified system. A Virtual Reality (VR) system is developed based on KD3, which is composed of interactive fire-knowledge transfer module and immersive fire training module. To verify the applicability and effectiveness of the established system, the interactive fire-knowledge transfer module was open to public for different tunnel users to learn, and a total of 50 participants were recruited to conduct VR training. Results verify the rationale of the developed system, as well as the proposed KD3 framework, demonstrating that the integration of knowledge learning and VR training significantly improves individuals’ evacuation decision-making and escape behavior during tunnel fires. These findings contribute to a paradigm shift in fire evacuation training by bridging the gap between theoretical learning and practical application. The study provides critical insights into human-centric emergency preparedness and offers practical guidance for future adaptive training systems in emergency.</div></div>","PeriodicalId":50461,"journal":{"name":"Expert Systems with Applications","volume":"273 ","pages":"Article 126895"},"PeriodicalIF":7.5,"publicationDate":"2025-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143429278","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Performing task automation for surgical robot: A spatial–temporal varying primal–dual neural network with guided obstacle avoidance and null space optimization
IF 7.5 1区 计算机科学
Expert Systems with Applications Pub Date : 2025-02-13 DOI: 10.1016/j.eswa.2025.126780
Xingqiang Jian , Bo Wu , Yibin Song , Dongdong Liu , Yu Wang , Wei Wang , Jingwei Zhao , Da He , Zhi Yang , Nan Zhang
{"title":"Performing task automation for surgical robot: A spatial–temporal varying primal–dual neural network with guided obstacle avoidance and null space optimization","authors":"Xingqiang Jian ,&nbsp;Bo Wu ,&nbsp;Yibin Song ,&nbsp;Dongdong Liu ,&nbsp;Yu Wang ,&nbsp;Wei Wang ,&nbsp;Jingwei Zhao ,&nbsp;Da He ,&nbsp;Zhi Yang ,&nbsp;Nan Zhang","doi":"10.1016/j.eswa.2025.126780","DOIUrl":"10.1016/j.eswa.2025.126780","url":null,"abstract":"<div><div>Performing surgical tasks safely and reliably presents significant challenges, including obstacle avoidance, joint limit constraints, and motion smoothness during the tool-target alignment (T-TA) stage, as well as precise tracking of preoperative plans during the execution of the preoperative planning surgery path (EPSP). The traditional inverse kinematics methods fall short in addressing these complex motion planning and control issues within the unstructured and time-varying surgical environment. Therefore, a novel spatial–temporal varying primal–dual neural network (STV-PDNN) that incorporates guided obstacle avoidance and null space optimization to address spatial–temporal constraints during surgery is proposed. Firstly, a velocity control quadratic programming (QP) framework based on target distance and orientation metrics is constructed by considering the relationships among the surgical robot, the environment, and the surgical target. Then, the STV-PDNN enables real-time problem-solving across two specific stages, employing velocity vector projection for obstacle avoidance and joint space obstacle avoidance velocity superposition to enhance the obstacle avoidance guidance. Furthermore, the joint null space optimization and maximum manipulability, along with a preoperative planning path velocity feed-forward and feedback velocity control mechanism, are integrated into the STV-PDNN structure. The improvement facilitates smoother, lower-energy joint movements and effective motion singularity avoidance during the T-TA stage, as well as precise motion control in the EPSP stage. The experiments conducted on the redundant robot Diana7 Med validate the effectiveness of the proposed method in autonomously executing T-TA and EPSP for pedicle screw implantation, offering a promising solution for the task autonomy of surgical robot.</div></div>","PeriodicalId":50461,"journal":{"name":"Expert Systems with Applications","volume":"273 ","pages":"Article 126780"},"PeriodicalIF":7.5,"publicationDate":"2025-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143428892","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
A coupled UAU-DKD-SIQS model considering partial and complete mapping relationship in time-varying multiplex networks
IF 7.5 1区 计算机科学
Expert Systems with Applications Pub Date : 2025-02-13 DOI: 10.1016/j.eswa.2025.126887
Yue Yu , Liang’an Huo
{"title":"A coupled UAU-DKD-SIQS model considering partial and complete mapping relationship in time-varying multiplex networks","authors":"Yue Yu ,&nbsp;Liang’an Huo","doi":"10.1016/j.eswa.2025.126887","DOIUrl":"10.1016/j.eswa.2025.126887","url":null,"abstract":"<div><div>During epidemics, official information and immunization behavior are crucial tools of controlling epidemic transmission. However, the interactions among official information, immunization behavior and epidemic are often asymmetric, and their coupled effects can vary over time, warranting further investigation. To explore these complexities, we propose a new coupled UAU-DKD-SIQS model to examine the impact of official information and immunization behavior under both partial and complete mapping relationships on epidemic transmission in time-varying multiplex networks. We focus on the asymmetrical activities of individuals in the processes of official information dissemination and epidemic transmission. Distinguishing from traditional research, we assume partial mapping between the information and behavior layers, partial mapping between the epidemic and information layers, and complete mapping between the behavior and epidemic layers. We then apply the Microscopic Markov Chain approach for theoretical analysis. Our findings indicate that enhancing the dissemination of official information, increasing the adoption of immunization behaviors, implementing quarantine measures, and strengthening policy support can all effectively control epidemic transmission. Notably, our results reveal the existence of a <em>meta</em>-critical point for epidemic outbreaks when considering the dynamics of immunization behavioral decision-making in relation to the mapping relationships influenced by the policy intensity of government information disclosure.</div></div>","PeriodicalId":50461,"journal":{"name":"Expert Systems with Applications","volume":"273 ","pages":"Article 126887"},"PeriodicalIF":7.5,"publicationDate":"2025-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143420568","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Relation enhancement for noise resistance in open-world link prediction
IF 7.5 1区 计算机科学
Expert Systems with Applications Pub Date : 2025-02-13 DOI: 10.1016/j.eswa.2025.126773
Jiang Xiaobo, Yongru Chen
{"title":"Relation enhancement for noise resistance in open-world link prediction","authors":"Jiang Xiaobo,&nbsp;Yongru Chen","doi":"10.1016/j.eswa.2025.126773","DOIUrl":"10.1016/j.eswa.2025.126773","url":null,"abstract":"<div><div>Open-world link prediction significantly expands the applicability of knowledge graphs by leveraging textual information to predict new entities. However, the transition from closed-world to open-world setting presents numerous new challenges, often resulting in a substantial decline in link prediction performance. It is important to investigate the causes of this decline. Through experiments assessing the impact of text noise on performance, it is found that text noise is the core factor leading to the degradation of prediction. Based on this finding, an effective anti-noise model enhanced by relation information is proposed. Firstly, a hierarchical gated fusion attention structure is designed to enhance the ability of the model to capture key semantic features by leveraging relational information in the knowledge graph, thereby significantly boosting its noise resistance. Secondly, this paper proposes a relation clustering algorithm for constructing relation specific mapping functions, which further enhances the utilization of relation information. Experimental results demonstrate that compared to similar mapping-based models, the proposed model exhibits a marked improvement in noise resistance. This method mitigates the negative impact of text noise on model performance and notably enhances the accuracy of open-world link prediction . These results show that improving noise resistance is highly consistent with improving link prediction performance in open-world scenarios. Finally, experiments show that the proposed model achieves the state-of-the-art among similar mapping-based models on two public datasets.</div></div>","PeriodicalId":50461,"journal":{"name":"Expert Systems with Applications","volume":"273 ","pages":"Article 126773"},"PeriodicalIF":7.5,"publicationDate":"2025-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143420466","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
相关产品
×
本文献相关产品
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信