Pub Date : 2018-08-01DOI: 10.1109/liss.2018.8593269
{"title":"LISS 2018 Index","authors":"","doi":"10.1109/liss.2018.8593269","DOIUrl":"https://doi.org/10.1109/liss.2018.8593269","url":null,"abstract":"","PeriodicalId":338998,"journal":{"name":"2018 8th International Conference on Logistics, Informatics and Service Sciences (LISS)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122457353","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 : 2018-08-01DOI: 10.1109/LISS.2018.8593231
Yi Sun, Zhao Pan
With the popularity of social networking, consumer often relies on social network when making purchase decisions. Despite the growing importance of social network in supporting online purchase behavior, there has been limited research focusing on the effect of social network on consumer collaborative purchase behavior. This paper proposes a framework for understanding consumer’s collaborative purchase behavior within online social groups. It is one of the first studies to our knowledge that explore the combined effect of social network structure and content on consumer’s collaborative purchase. In this study, we first extract and analyze adjacent matrix, which representing related social networks, from a large dataset. This is then combined with interaction-based content analysis to identify the structure of social network. After verifying the impact of network attributes and structure on consumer purchases, we conducted content analysis based on chat records and identified productrelated interaction structures and content composition information based on the language action perspective. Finally, we combine content analysis with network topology analysis to construct a weighted social network and calculate the impact of these social networks on consumer purchasing behavior. Our research proposes a research framework to effectively collect, extract and analyze the structure and content of social networks.
{"title":"The Impact of Social Network: Understand Consumer’s Collaborative Purchase Behavior","authors":"Yi Sun, Zhao Pan","doi":"10.1109/LISS.2018.8593231","DOIUrl":"https://doi.org/10.1109/LISS.2018.8593231","url":null,"abstract":"With the popularity of social networking, consumer often relies on social network when making purchase decisions. Despite the growing importance of social network in supporting online purchase behavior, there has been limited research focusing on the effect of social network on consumer collaborative purchase behavior. This paper proposes a framework for understanding consumer’s collaborative purchase behavior within online social groups. It is one of the first studies to our knowledge that explore the combined effect of social network structure and content on consumer’s collaborative purchase. In this study, we first extract and analyze adjacent matrix, which representing related social networks, from a large dataset. This is then combined with interaction-based content analysis to identify the structure of social network. After verifying the impact of network attributes and structure on consumer purchases, we conducted content analysis based on chat records and identified productrelated interaction structures and content composition information based on the language action perspective. Finally, we combine content analysis with network topology analysis to construct a weighted social network and calculate the impact of these social networks on consumer purchasing behavior. Our research proposes a research framework to effectively collect, extract and analyze the structure and content of social networks.","PeriodicalId":338998,"journal":{"name":"2018 8th International Conference on Logistics, Informatics and Service Sciences (LISS)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115310894","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 : 2018-08-01DOI: 10.1109/liss.2018.8593261
{"title":"LISS 2018 Proceeding","authors":"","doi":"10.1109/liss.2018.8593261","DOIUrl":"https://doi.org/10.1109/liss.2018.8593261","url":null,"abstract":"","PeriodicalId":338998,"journal":{"name":"2018 8th International Conference on Logistics, Informatics and Service Sciences (LISS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130153044","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}
Focusing on the overlapping areas of the logistics industry with a large number of mature blockchain applications and the public welfare industry that requires high transparency and credibility, this paper designs and implements an innovative philanthropy logistics platform based on blockchain technology through the Ethereum platform. Our platform makes use of the open, transparent, and irrevocable features of the blockchain, combined with a unique Responsibility Relay System and Evaluation and Reporting Mechanism, and can achieve the consistency of the data on the chain with real-world status, as well as the authenticity and transparency of philanthropy logistics data. This paper also establishes a model for evaluating philanthropy material donations for social welfare based on the classic network maximum flow algorithm. After four months of empirical analysis, we have concluded that the blockchain platform can greatly increase the user's trust in the project, enhance the system's cleanliness coefficient and increase the quality of philanthropically raised materials, thereby improving the public welfare of charitable donations. The paper draws the conclusion that this blockchain platform is a technical solution for maximizing social welfare.
{"title":"Public Philanthropy Logistics Platform Based on Blockchain Technology for Social Welfare Maximization","authors":"Jiafeng Li, Fuyang Qu, Xin Tu, T. Fu, Jiayan Guo, Jian-ming Zhu","doi":"10.1109/LISS.2018.8593217","DOIUrl":"https://doi.org/10.1109/LISS.2018.8593217","url":null,"abstract":"Focusing on the overlapping areas of the logistics industry with a large number of mature blockchain applications and the public welfare industry that requires high transparency and credibility, this paper designs and implements an innovative philanthropy logistics platform based on blockchain technology through the Ethereum platform. Our platform makes use of the open, transparent, and irrevocable features of the blockchain, combined with a unique Responsibility Relay System and Evaluation and Reporting Mechanism, and can achieve the consistency of the data on the chain with real-world status, as well as the authenticity and transparency of philanthropy logistics data. This paper also establishes a model for evaluating philanthropy material donations for social welfare based on the classic network maximum flow algorithm. After four months of empirical analysis, we have concluded that the blockchain platform can greatly increase the user's trust in the project, enhance the system's cleanliness coefficient and increase the quality of philanthropically raised materials, thereby improving the public welfare of charitable donations. The paper draws the conclusion that this blockchain platform is a technical solution for maximizing social welfare.","PeriodicalId":338998,"journal":{"name":"2018 8th International Conference on Logistics, Informatics and Service Sciences (LISS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126928118","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 : 2018-08-01DOI: 10.1109/liss.2018.8593260
{"title":"LISS 2018 Copyright Page","authors":"","doi":"10.1109/liss.2018.8593260","DOIUrl":"https://doi.org/10.1109/liss.2018.8593260","url":null,"abstract":"","PeriodicalId":338998,"journal":{"name":"2018 8th International Conference on Logistics, Informatics and Service Sciences (LISS)","volume":"81 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128273336","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 : 2018-08-01DOI: 10.1109/LISS.2018.8593216
Duo Qin, Lei Huang, Y. Wang
The large number of systems of the railway in China produced much complex and diverse data which are in various formats, scattered storage, and have a big difficulty in data sharing. Existing researches indicate that metadata management is useful to solve these problems. This paper by analyzing the types of metadata, makes a metadata content model and creates a standard for metadata standardization and exchange based on the CWM for the metadata of railway. Besides, we build the architecture and functions of the metadata system, and successfully designed a metadata management system which is beneficial to the data management for the railway systems.
{"title":"Construction of Railway Metadata Management System Based on Metadata Content Model and CWM Exchange Mechanism","authors":"Duo Qin, Lei Huang, Y. Wang","doi":"10.1109/LISS.2018.8593216","DOIUrl":"https://doi.org/10.1109/LISS.2018.8593216","url":null,"abstract":"The large number of systems of the railway in China produced much complex and diverse data which are in various formats, scattered storage, and have a big difficulty in data sharing. Existing researches indicate that metadata management is useful to solve these problems. This paper by analyzing the types of metadata, makes a metadata content model and creates a standard for metadata standardization and exchange based on the CWM for the metadata of railway. Besides, we build the architecture and functions of the metadata system, and successfully designed a metadata management system which is beneficial to the data management for the railway systems.","PeriodicalId":338998,"journal":{"name":"2018 8th International Conference on Logistics, Informatics and Service Sciences (LISS)","volume":"174 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131605915","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 : 2018-08-01DOI: 10.1109/LISS.2018.8593225
Zuan Wang, Youliang Tian, Jian-ming Zhu
The existing data sharing models have some issues such as poor transparency of data transactions, data without security assurance and lacking of effective data tracking methods. This paper proposed a brand-new data sharing scheme based on blockchain technology. Firstly, a blockchain double-chain structure about blockchain was introduced, one chain was used to store the original data and another was used to store transaction data generated by transactions. This structure separated the original data storage and data transactions. Secondly, combined with proxy re-encryption technology, safe and reliable data sharing were achieved. Finally, a new design was implemented. The logical structure of data transaction records enables data to be traced. The results of correctness and security analysis showed that this scheme can provide new technical ideas and methods for big data sharing and data trace.
{"title":"Data Sharing and Tracing Scheme Based on Blockchain","authors":"Zuan Wang, Youliang Tian, Jian-ming Zhu","doi":"10.1109/LISS.2018.8593225","DOIUrl":"https://doi.org/10.1109/LISS.2018.8593225","url":null,"abstract":"The existing data sharing models have some issues such as poor transparency of data transactions, data without security assurance and lacking of effective data tracking methods. This paper proposed a brand-new data sharing scheme based on blockchain technology. Firstly, a blockchain double-chain structure about blockchain was introduced, one chain was used to store the original data and another was used to store transaction data generated by transactions. This structure separated the original data storage and data transactions. Secondly, combined with proxy re-encryption technology, safe and reliable data sharing were achieved. Finally, a new design was implemented. The logical structure of data transaction records enables data to be traced. The results of correctness and security analysis showed that this scheme can provide new technical ideas and methods for big data sharing and data trace.","PeriodicalId":338998,"journal":{"name":"2018 8th International Conference on Logistics, Informatics and Service Sciences (LISS)","volume":"28 6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133736200","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 : 2018-08-01DOI: 10.1109/LISS.2018.8593212
B. Dan, X. Luo, Ru Liu, Shuguang Zhang
Considering a product service supply chain (PSSC) that consists of a manufacturer and an integrator of sales and after-sales service in which the demand of product is influenced by both the product quality and service level, we set up a decision optimization model and obtain the optimal equilibrium solutions under decentralized and centralized decision-making respectively. We further incorporate a two-way cost sharing and fixed transfer payment contract to coordinate the supply chain. The conclusions show that this coordination contract can coordinate the supply chain and achieve Pareto improvement when the contract parameters under certain conditions. The effect of wholesale price on the profit of both is the key to eliminate the double marginalization effect. We find that when the influence of service level on demand becomes greater, profits of both the manufacturer and the integrator become larger.
{"title":"The Optimal Strategies in a Product Service Supply Chain with Product Quality and Service Level Affecting Sales","authors":"B. Dan, X. Luo, Ru Liu, Shuguang Zhang","doi":"10.1109/LISS.2018.8593212","DOIUrl":"https://doi.org/10.1109/LISS.2018.8593212","url":null,"abstract":"Considering a product service supply chain (PSSC) that consists of a manufacturer and an integrator of sales and after-sales service in which the demand of product is influenced by both the product quality and service level, we set up a decision optimization model and obtain the optimal equilibrium solutions under decentralized and centralized decision-making respectively. We further incorporate a two-way cost sharing and fixed transfer payment contract to coordinate the supply chain. The conclusions show that this coordination contract can coordinate the supply chain and achieve Pareto improvement when the contract parameters under certain conditions. The effect of wholesale price on the profit of both is the key to eliminate the double marginalization effect. We find that when the influence of service level on demand becomes greater, profits of both the manufacturer and the integrator become larger.","PeriodicalId":338998,"journal":{"name":"2018 8th International Conference on Logistics, Informatics and Service Sciences (LISS)","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124876996","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 : 2018-08-01DOI: 10.1109/LISS.2018.8593222
Xiaonan Gao, Sen Wu
Clustering algorithm for binary data is a challenging problem in data mining and machine learning fields. While some efforts have been made to deal with clustering binary data, they lack effective methods to balance clustering quality and efficiency. To this end, we propose a hierarchical clustering algorithm for binary data based on cosine similarity (HABOC) in this paper. Firstly, we assess similarity between data objects with binary attributes using Cosine Similarity (CS). Then, the Cosine Similarity of a Set (CSS) is defined to compute similarity of a set containing multiple objects. Based on CSS, we propose the Cosine Feature Vector of a Set (CFVS) and additivity of CFVS to compress data and merge two clusters directly. We also exploit hierarchical clustering method to implement clustering, in order to avoid the sensitivity to the order of data objects and algorithm parameters. Experimental results on several UCI datasets demonstrate that HABOC outperforms existing binary data clustering algorithms.
二进制数据的聚类算法是数据挖掘和机器学习领域的一个具有挑战性的问题。虽然在处理二进制数据聚类方面已经做了一些努力，但缺乏有效的方法来平衡聚类的质量和效率。为此，本文提出了一种基于余弦相似度(HABOC)的二值数据分层聚类算法。首先，我们使用余弦相似度(CS)来评估具有二元属性的数据对象之间的相似度。然后，定义了集的余弦相似度(cos Similarity of a Set, CSS)来计算包含多个对象的集的相似度。在CSS的基础上，我们提出了集的余弦特征向量(CFVS)和CFVS的可加性来直接压缩和合并两个聚类。为了避免对数据对象顺序和算法参数的敏感性，我们还利用层次聚类方法来实现聚类。在多个UCI数据集上的实验结果表明，HABOC算法优于现有的二进制数据聚类算法。
{"title":"Hierarchical Clustering Algorithm for Binary Data Based on Cosine Similarity","authors":"Xiaonan Gao, Sen Wu","doi":"10.1109/LISS.2018.8593222","DOIUrl":"https://doi.org/10.1109/LISS.2018.8593222","url":null,"abstract":"Clustering algorithm for binary data is a challenging problem in data mining and machine learning fields. While some efforts have been made to deal with clustering binary data, they lack effective methods to balance clustering quality and efficiency. To this end, we propose a hierarchical clustering algorithm for binary data based on cosine similarity (HABOC) in this paper. Firstly, we assess similarity between data objects with binary attributes using Cosine Similarity (CS). Then, the Cosine Similarity of a Set (CSS) is defined to compute similarity of a set containing multiple objects. Based on CSS, we propose the Cosine Feature Vector of a Set (CFVS) and additivity of CFVS to compress data and merge two clusters directly. We also exploit hierarchical clustering method to implement clustering, in order to avoid the sensitivity to the order of data objects and algorithm parameters. Experimental results on several UCI datasets demonstrate that HABOC outperforms existing binary data clustering algorithms.","PeriodicalId":338998,"journal":{"name":"2018 8th International Conference on Logistics, Informatics and Service Sciences (LISS)","volume":"342 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115883117","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 : 2018-08-01DOI: 10.1109/LISS.2018.8593215
Yue Huang
With the rapid development of mobile Internet, the growth amount of data has exploded, and data mining has played an increasingly important role in data analyzing. More and more researches have been done on data mining. Detecting intellectual structure of data mining research is of significance in understanding its research topics and research fronts. Focusing on the method of bibliographic coupling analysis, this paper explores the intellectual structure of data mining during 2007-2016, based on 12625 cleaned bibliographic data of data mining-related articles retrieved from Web of Science. Experiments results show that there are mainly 10 research topics in the field of data mining, such as classification, frequent pattern mining and clustering, among which the first three topics are the research on domain of data mining itself, and the last seven topics are the research on data mining applications.
随着移动互联网的快速发展，数据量呈爆炸式增长，数据挖掘在数据分析中发挥着越来越重要的作用。关于数据挖掘的研究越来越多。检测数据挖掘研究的智力结构对于理解其研究课题和研究前沿具有重要意义。本文以Web of Science检索到的12625篇数据挖掘相关文章为研究对象，采用书目耦合分析方法，对2007-2016年数据挖掘的知识结构进行了研究。实验结果表明，目前数据挖掘领域主要有分类、频繁模式挖掘和聚类等10个研究课题，其中前3个课题是对数据挖掘领域本身的研究，后7个课题是对数据挖掘应用的研究。
{"title":"Intellectual Structure of Research on Data Mining Using Bibliographic Coupling Analysis","authors":"Yue Huang","doi":"10.1109/LISS.2018.8593215","DOIUrl":"https://doi.org/10.1109/LISS.2018.8593215","url":null,"abstract":"With the rapid development of mobile Internet, the growth amount of data has exploded, and data mining has played an increasingly important role in data analyzing. More and more researches have been done on data mining. Detecting intellectual structure of data mining research is of significance in understanding its research topics and research fronts. Focusing on the method of bibliographic coupling analysis, this paper explores the intellectual structure of data mining during 2007-2016, based on 12625 cleaned bibliographic data of data mining-related articles retrieved from Web of Science. Experiments results show that there are mainly 10 research topics in the field of data mining, such as classification, frequent pattern mining and clustering, among which the first three topics are the research on domain of data mining itself, and the last seven topics are the research on data mining applications.","PeriodicalId":338998,"journal":{"name":"2018 8th International Conference on Logistics, Informatics and Service Sciences (LISS)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116437901","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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