Liuyang Zhao, Yezhou Sha, Kaiwen Zhang, Jiaxin Yang
Blockchain and distributed ledger technologies have attracted massive attention from both legal communities and businesses. Asset securitization is the procedure in which an issuer designs a financial instrument that is marketable by combining or merging different financial assets into one group. However, most securitization occurs with loans and other assets that generate receivables, such as consumer or business debt of various types. This article discusses the possible benefits of blockchain during the securitization process using the deep learning-based adaptive online intelligent framework (DLAOIF). The benefits can be significant, from reduced costs, time, and fraud risks to increased safety, trust, and accuracy. Tracking financial assets on a blockchain can reduce dependence on credit rating organizations and allow investors to monitor asset performance and the associated risk more carefully. It should improve investor confidence and increase secondary market interest.
{"title":"Deep Learning-Based Adaptive Online Intelligent Framework for a Blockchain Application in Risk Control of Asset Securitization","authors":"Liuyang Zhao, Yezhou Sha, Kaiwen Zhang, Jiaxin Yang","doi":"10.4018/ijdwm.323182","DOIUrl":"https://doi.org/10.4018/ijdwm.323182","url":null,"abstract":"Blockchain and distributed ledger technologies have attracted massive attention from both legal communities and businesses. Asset securitization is the procedure in which an issuer designs a financial instrument that is marketable by combining or merging different financial assets into one group. However, most securitization occurs with loans and other assets that generate receivables, such as consumer or business debt of various types. This article discusses the possible benefits of blockchain during the securitization process using the deep learning-based adaptive online intelligent framework (DLAOIF). The benefits can be significant, from reduced costs, time, and fraud risks to increased safety, trust, and accuracy. Tracking financial assets on a blockchain can reduce dependence on credit rating organizations and allow investors to monitor asset performance and the associated risk more carefully. It should improve investor confidence and increase secondary market interest.","PeriodicalId":54963,"journal":{"name":"International Journal of Data Warehousing and Mining","volume":null,"pages":null},"PeriodicalIF":1.2,"publicationDate":"2023-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46545889","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
With the acceleration of the urbanization process, the traditional urban management has become increasingly unable to meet the needs of urban management and development. At the same time, with the rapid development of artificial intelligence (AI) and big data (BD), the use of AI and BD to analyze cities has been gradually emerging. Therefore, this paper used AI and BD to study the optimization method of sustainable development of smart city public management. The research showed that the respondents in N, Z, and S cities were 60.67%, 60.07%, and 60.31% satisfied with the handling of events by urban public management subjects, respectively. The experts' evaluation scores on the feasibility and effectiveness of urban public management optimization strategies were 88.79 and 92.82, respectively. The public's satisfaction with the smart city public management subject's handling of events was still not high enough. The optimization strategy for sustainable development of smart city public management proposed in this paper with BD had certain practical value.
{"title":"Optimization Method for Sustainable Development of Smart City Public Management Based on Big Data Analysis","authors":"Wen Wang, Lin Li","doi":"10.4018/ijdwm.322757","DOIUrl":"https://doi.org/10.4018/ijdwm.322757","url":null,"abstract":"With the acceleration of the urbanization process, the traditional urban management has become increasingly unable to meet the needs of urban management and development. At the same time, with the rapid development of artificial intelligence (AI) and big data (BD), the use of AI and BD to analyze cities has been gradually emerging. Therefore, this paper used AI and BD to study the optimization method of sustainable development of smart city public management. The research showed that the respondents in N, Z, and S cities were 60.67%, 60.07%, and 60.31% satisfied with the handling of events by urban public management subjects, respectively. The experts' evaluation scores on the feasibility and effectiveness of urban public management optimization strategies were 88.79 and 92.82, respectively. The public's satisfaction with the smart city public management subject's handling of events was still not high enough. The optimization strategy for sustainable development of smart city public management proposed in this paper with BD had certain practical value.","PeriodicalId":54963,"journal":{"name":"International Journal of Data Warehousing and Mining","volume":null,"pages":null},"PeriodicalIF":1.2,"publicationDate":"2023-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86772466","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
With the innovation of information technology, digital stadiums and gymnasiums are based on independent innovation, information management, and intelligent cultivation and development, which promotes the construction of a new ecology of intelligent sports and also determines the development situation and development mode of traditional sports. In the construction of intelligent service mode of digital stadiums and gymnasiums in the context of smart cities, the management information system, as the application support of stadium information technology, is the key channel to improve the intelligent level of stadiums and gymnasiums. The establishment and promotion of a smart management information system is an inevitable trend for smart stadiums and gymnasiums to complete key technologies, consumer experience, and efficient functional innovation of management methods, which is also an important content of science and technology-enabling stadiums and gymnasiums. This paper proposed the research on intelligent service mode of digital stadiums and gymnasiums under the background of smart cities.
{"title":"Investigation of Intelligent Service Mode of Digital Stadiums and Gymnasiums in the Context of Smart Cities","authors":"W. Zhang","doi":"10.4018/ijdwm.322393","DOIUrl":"https://doi.org/10.4018/ijdwm.322393","url":null,"abstract":"With the innovation of information technology, digital stadiums and gymnasiums are based on independent innovation, information management, and intelligent cultivation and development, which promotes the construction of a new ecology of intelligent sports and also determines the development situation and development mode of traditional sports. In the construction of intelligent service mode of digital stadiums and gymnasiums in the context of smart cities, the management information system, as the application support of stadium information technology, is the key channel to improve the intelligent level of stadiums and gymnasiums. The establishment and promotion of a smart management information system is an inevitable trend for smart stadiums and gymnasiums to complete key technologies, consumer experience, and efficient functional innovation of management methods, which is also an important content of science and technology-enabling stadiums and gymnasiums. This paper proposed the research on intelligent service mode of digital stadiums and gymnasiums under the background of smart cities.","PeriodicalId":54963,"journal":{"name":"International Journal of Data Warehousing and Mining","volume":null,"pages":null},"PeriodicalIF":1.2,"publicationDate":"2023-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77303367","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The main task of aspect-based sentiment analysis is to determine the sentiment polarity of a given aspect in the sentence. A major issue lies in identifying the aspect sentiment is to establish the relationship between the aspect and its opinion words. The application of syntactic dependency trees is one such resolution. However, the widely-used dependency parsers still have challenges in obtaining a solid sentiment classification result. In this work, an information propagation graph convolutional network based on syntactic structure optimization is proposed on the task of ABSA. To further complement the syntactic information, the semantic information is incorporated to learn the representations using graph information propagation mechanism. In addition, the effects of syntactic and semantic information are adapted via feature separation. Experimental results on three benchmark datasets show that the proposed model achieves satisfying performance against the state-of-the-art methods, indicating that the model can precisely build the relation between aspect and its context words.
{"title":"Structure Graph Refined Information Propagate Network for Aspect-Based Sentiment Analysis","authors":"Weihao Huang, Shaohua Cai, Haoran Li, Qianhua Cai","doi":"10.4018/ijdwm.321107","DOIUrl":"https://doi.org/10.4018/ijdwm.321107","url":null,"abstract":"The main task of aspect-based sentiment analysis is to determine the sentiment polarity of a given aspect in the sentence. A major issue lies in identifying the aspect sentiment is to establish the relationship between the aspect and its opinion words. The application of syntactic dependency trees is one such resolution. However, the widely-used dependency parsers still have challenges in obtaining a solid sentiment classification result. In this work, an information propagation graph convolutional network based on syntactic structure optimization is proposed on the task of ABSA. To further complement the syntactic information, the semantic information is incorporated to learn the representations using graph information propagation mechanism. In addition, the effects of syntactic and semantic information are adapted via feature separation. Experimental results on three benchmark datasets show that the proposed model achieves satisfying performance against the state-of-the-art methods, indicating that the model can precisely build the relation between aspect and its context words.","PeriodicalId":54963,"journal":{"name":"International Journal of Data Warehousing and Mining","volume":null,"pages":null},"PeriodicalIF":1.2,"publicationDate":"2023-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76880828","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Identifying the places an infected person has visited during a virus incubation time in order to conduct contact tracing is currently done using manual interviews since proximity-based contact tracing methods do not store geolocation information due to privacy concerns. During the incubation time, an infected person might visit several locations and either forget where they went or are reluctant to disclose their trip details. To minimize manual location tracing while preserving the user's privacy, the authors propose a mesh block sequence method where the trajectories are transformed into a mesh block sequence before being shared with health authorities. These simulations show that this a useful method by which to protect user privacy by concealing specific details related to a trajectory. While this simulation uses an Australian administrative region structure, this method is applicable in countries which implement similar administrative hierarchical building blocks.
{"title":"Contact Tracing With District-Based Trajectories","authors":"Kiki Adhinugraha, W. Rahayu, Nasser Allheeib","doi":"10.4018/ijdwm.321197","DOIUrl":"https://doi.org/10.4018/ijdwm.321197","url":null,"abstract":"Identifying the places an infected person has visited during a virus incubation time in order to conduct contact tracing is currently done using manual interviews since proximity-based contact tracing methods do not store geolocation information due to privacy concerns. During the incubation time, an infected person might visit several locations and either forget where they went or are reluctant to disclose their trip details. To minimize manual location tracing while preserving the user's privacy, the authors propose a mesh block sequence method where the trajectories are transformed into a mesh block sequence before being shared with health authorities. These simulations show that this a useful method by which to protect user privacy by concealing specific details related to a trajectory. While this simulation uses an Australian administrative region structure, this method is applicable in countries which implement similar administrative hierarchical building blocks.","PeriodicalId":54963,"journal":{"name":"International Journal of Data Warehousing and Mining","volume":null,"pages":null},"PeriodicalIF":1.2,"publicationDate":"2023-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84196746","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Health budget allocation choices are increasingly aided by medical technology's economic evaluation (EE). With thousands of new items launched each year, the medical device (MD) business is one of the most active domains of medical advancement among providers of innovation. Some of these considerations have to do with the specifics of how the gadget works. The paper examines the investment assessment of new medical devices from an industrial viewpoint. The strategy EE-MD presented should lead to more inventive and cost-effective surgical supplies for the medical industry. The study's purpose is to better the decision-making process for medical device development. Small and medium-sized firms are a crucial source of innovation for the future, and the research focuses mostly on them. Design economy and professional engineering literature are linked in the article. The proposed multi-attribute and team method to construct selection discusses the financial factor and provides a strong foundation for ongoing program management by identifying project-specific risks and strategic alliances.
{"title":"Resilience of a Supply Chain-Based Economic Evaluation of Medical Devices From an Industry Perspective","authors":"Yu Yang, Zecheng Yin","doi":"10.4018/ijdwm.320761","DOIUrl":"https://doi.org/10.4018/ijdwm.320761","url":null,"abstract":"Health budget allocation choices are increasingly aided by medical technology's economic evaluation (EE). With thousands of new items launched each year, the medical device (MD) business is one of the most active domains of medical advancement among providers of innovation. Some of these considerations have to do with the specifics of how the gadget works. The paper examines the investment assessment of new medical devices from an industrial viewpoint. The strategy EE-MD presented should lead to more inventive and cost-effective surgical supplies for the medical industry. The study's purpose is to better the decision-making process for medical device development. Small and medium-sized firms are a crucial source of innovation for the future, and the research focuses mostly on them. Design economy and professional engineering literature are linked in the article. The proposed multi-attribute and team method to construct selection discusses the financial factor and provides a strong foundation for ongoing program management by identifying project-specific risks and strategic alliances.","PeriodicalId":54963,"journal":{"name":"International Journal of Data Warehousing and Mining","volume":null,"pages":null},"PeriodicalIF":1.2,"publicationDate":"2023-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88238947","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Accounting information systems (AIS) gather, store, and analyze data in providing information to business leaders. Information technology resources and a computer-based accounting system are often used to monitor accounting activities in an accounting information system. Supply chain management strategies, planning, and implementation are increasingly dependent on the expertise of accountants with globalization. The accountant's job is to assist the supply chain design, development, and implementation group. Top management commitment, the kind of accounting information systems used, and input controls are all factors that affect accounting information systems' data quality. They can trace any form of theft or misappropriation using the blockchain (BC), which maintains asset transfers. In hopes of avoiding fraud, agreements loaded with economics and finance principles might be used to govern corporate operations. Using internet of things (IoT) data, banks can better understand their customers' business demands and value chain.
{"title":"Resilient Supply Chains to Improve the Integrity of Accounting Data in Financial Institutions Worldwide Using Blockchain Technology","authors":"Yu Yang, Zecheng Yin","doi":"10.4018/ijdwm.320648","DOIUrl":"https://doi.org/10.4018/ijdwm.320648","url":null,"abstract":"Accounting information systems (AIS) gather, store, and analyze data in providing information to business leaders. Information technology resources and a computer-based accounting system are often used to monitor accounting activities in an accounting information system. Supply chain management strategies, planning, and implementation are increasingly dependent on the expertise of accountants with globalization. The accountant's job is to assist the supply chain design, development, and implementation group. Top management commitment, the kind of accounting information systems used, and input controls are all factors that affect accounting information systems' data quality. They can trace any form of theft or misappropriation using the blockchain (BC), which maintains asset transfers. In hopes of avoiding fraud, agreements loaded with economics and finance principles might be used to govern corporate operations. Using internet of things (IoT) data, banks can better understand their customers' business demands and value chain.","PeriodicalId":54963,"journal":{"name":"International Journal of Data Warehousing and Mining","volume":null,"pages":null},"PeriodicalIF":1.2,"publicationDate":"2023-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82361034","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The data under the smart city spatio-temporal big data platform is very diverse, and there are many modern spatial and spatial databases in the archives management system related to natural resources. Big data can effectively improve the quality and classification of natural resource archives management (referred to as NRAM for convenience of description). However, the traditional NRAM method and informatization level can no longer meet the needs of the current NRAM, so people must continue to make efforts to digitize the natural resource archives. To this end, this paper analyzed the characteristics and problems of NRAM and then used the big data platform to make corresponding management adjustments to promote the development of NRAM. Under big data, the degree of management improvement and management efficiency were better than the original NRAM, and the degree of management improvement was 14% higher than the original NRAM. In short, both big data and artificial intelligence can improve the integrated management of natural resource archives.
{"title":"Digital Management Strategy of Natural Resource Archives Under Smart City Space-Time Big Data Platform","authors":"Y. Wang, Pin Lv","doi":"10.4018/ijdwm.320649","DOIUrl":"https://doi.org/10.4018/ijdwm.320649","url":null,"abstract":"The data under the smart city spatio-temporal big data platform is very diverse, and there are many modern spatial and spatial databases in the archives management system related to natural resources. Big data can effectively improve the quality and classification of natural resource archives management (referred to as NRAM for convenience of description). However, the traditional NRAM method and informatization level can no longer meet the needs of the current NRAM, so people must continue to make efforts to digitize the natural resource archives. To this end, this paper analyzed the characteristics and problems of NRAM and then used the big data platform to make corresponding management adjustments to promote the development of NRAM. Under big data, the degree of management improvement and management efficiency were better than the original NRAM, and the degree of management improvement was 14% higher than the original NRAM. In short, both big data and artificial intelligence can improve the integrated management of natural resource archives.","PeriodicalId":54963,"journal":{"name":"International Journal of Data Warehousing and Mining","volume":null,"pages":null},"PeriodicalIF":1.2,"publicationDate":"2023-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84675167","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Artificial intelligence (AI) is the primary tool used by businesses to enhance economic advantages. Family company management is undergoing information and the digital industrial revolution because of artificial intelligence. With the fast development of new technologies, the family company management style has a significant effect and previously unimaginable impact. For most enterprises, intergenerational succession is either taking place or will occur shortly. Here intergenerational inheritance significance for family-owned businesses (IISF-OB) has been proposed to solve family company performance and the internal action mechanisms. Intergenerational succession pathways deserve consideration, and research for the family businesses must utilize artificial intelligence technology to enhance related work. The proposed method investigates how family company management modes can be innovated to fulfill societal development requirements methods in artificial intelligence. It will use case studies, comparative analyses, and develop a new solution.
{"title":"Analysis on the Allocation of Control Right of Intergenerational Inheritance of Family Enterprises in the New Era","authors":"Zhanzhong Wang, Jiajun Li","doi":"10.4018/ijdwm.319966","DOIUrl":"https://doi.org/10.4018/ijdwm.319966","url":null,"abstract":"Artificial intelligence (AI) is the primary tool used by businesses to enhance economic advantages. Family company management is undergoing information and the digital industrial revolution because of artificial intelligence. With the fast development of new technologies, the family company management style has a significant effect and previously unimaginable impact. For most enterprises, intergenerational succession is either taking place or will occur shortly. Here intergenerational inheritance significance for family-owned businesses (IISF-OB) has been proposed to solve family company performance and the internal action mechanisms. Intergenerational succession pathways deserve consideration, and research for the family businesses must utilize artificial intelligence technology to enhance related work. The proposed method investigates how family company management modes can be innovated to fulfill societal development requirements methods in artificial intelligence. It will use case studies, comparative analyses, and develop a new solution.","PeriodicalId":54963,"journal":{"name":"International Journal of Data Warehousing and Mining","volume":null,"pages":null},"PeriodicalIF":1.2,"publicationDate":"2023-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77516727","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Efficient and convenient vulnerability detection for smart contracts is a key issue in the field of smart contracts. The earlier vulnerability detection for smart contracts mainly relies on static symbol analysis, which has high accuracy but low efficiency and is prone to path explosion. In this paper, the authors propose a static method for vulnerability detection based on deep learning. It first disassembles Ethereum smart contracts into opcode sequences and then converts the vulnerability detection problem into a natural language text classification problem. The word vector method is employed to map each opcode to a uniform vector space, and the opcode sequence matrix is trained by the TextCNN method to detect vulnerabilities. Furthermore, a code obfuscation method is given to enhance and balance the dataset, while three different opcode sequence generation methods are proposed to construct features. The experimental results verify that the average prediction accuracy of each smart contract exceeds 96%, and the average detection time is less than 0.1 s.
{"title":"An Efficient Code-Embedding-Based Vulnerability Detection Model for Ethereum Smart Contracts","authors":"Zhigang Xu, Xingxing Chen, Xinhua Dong, Hongmu Han, Zhongzhen Yan, Kangze Ye, Chaojun Li, Zhiqiang Zheng, Haitao Wang, Jiaxi Zhang","doi":"10.4018/ijdwm.320473","DOIUrl":"https://doi.org/10.4018/ijdwm.320473","url":null,"abstract":"Efficient and convenient vulnerability detection for smart contracts is a key issue in the field of smart contracts. The earlier vulnerability detection for smart contracts mainly relies on static symbol analysis, which has high accuracy but low efficiency and is prone to path explosion. In this paper, the authors propose a static method for vulnerability detection based on deep learning. It first disassembles Ethereum smart contracts into opcode sequences and then converts the vulnerability detection problem into a natural language text classification problem. The word vector method is employed to map each opcode to a uniform vector space, and the opcode sequence matrix is trained by the TextCNN method to detect vulnerabilities. Furthermore, a code obfuscation method is given to enhance and balance the dataset, while three different opcode sequence generation methods are proposed to construct features. The experimental results verify that the average prediction accuracy of each smart contract exceeds 96%, and the average detection time is less than 0.1 s.","PeriodicalId":54963,"journal":{"name":"International Journal of Data Warehousing and Mining","volume":null,"pages":null},"PeriodicalIF":1.2,"publicationDate":"2023-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82151250","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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