We study the integration of individuals attributes to infer their influence ability in social network in this paper. The influence between individuals is usually asymmetric and can propagate via edges gradually. We suggest an Influence Factor Graph(IFG) which can integrate different node and edge features into a uniform inferring model. And for each node the model can compute personalized influence ability value. Experiment results in Zarchary and Wikipedia co-editing social networks show that, the model can depict influence reasonably and reveal some interesting social influence rules.
{"title":"Inferring Individual Influence in Social Network","authors":"Haisu Zhang, Wenyan Gan, Feng Xu","doi":"10.1109/WISA.2012.53","DOIUrl":"https://doi.org/10.1109/WISA.2012.53","url":null,"abstract":"We study the integration of individuals attributes to infer their influence ability in social network in this paper. The influence between individuals is usually asymmetric and can propagate via edges gradually. We suggest an Influence Factor Graph(IFG) which can integrate different node and edge features into a uniform inferring model. And for each node the model can compute personalized influence ability value. Experiment results in Zarchary and Wikipedia co-editing social networks show that, the model can depict influence reasonably and reveal some interesting social influence rules.","PeriodicalId":313228,"journal":{"name":"2012 Ninth Web Information Systems and Applications Conference","volume":"86 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123595381","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}
This article is composed in the background of the study of scientific field of coauthors phenomenon factual basis. By the study of massive amounts of relational data, it provides us with major significances theoretically and practically on retrieving and obtaining professionally academic information and getting knowing of academic development trend of miscellaneous fields. In process of studying this type of project, the problem of cluttering for coauthors that are in the data is involved. However, it is hard to meet the need of implementing the analysis of massive amounts of data cluttering by the existing cluttering software and algorithms, for this reason, finding an approach to deal with this kind of question is toughly important. To solve this question, this article presents an optimized Bisecting K-Means (BKM) clustering algorithm based on Hadoop and states the fashion of how to optimize the algorithm and the key point of implementing in details after analyzing the status quo related to this study. Estimating the complexity of the algorithm by experiments indicates the current problems and the direction for the future study.
{"title":"Implementation of Space Optimized Bisecting K-Means (BKM) Based on Hadoop","authors":"Y. Yin, Chengguang Wei, Guigang Zhang, C. Li","doi":"10.1109/WISA.2012.47","DOIUrl":"https://doi.org/10.1109/WISA.2012.47","url":null,"abstract":"This article is composed in the background of the study of scientific field of coauthors phenomenon factual basis. By the study of massive amounts of relational data, it provides us with major significances theoretically and practically on retrieving and obtaining professionally academic information and getting knowing of academic development trend of miscellaneous fields. In process of studying this type of project, the problem of cluttering for coauthors that are in the data is involved. However, it is hard to meet the need of implementing the analysis of massive amounts of data cluttering by the existing cluttering software and algorithms, for this reason, finding an approach to deal with this kind of question is toughly important. To solve this question, this article presents an optimized Bisecting K-Means (BKM) clustering algorithm based on Hadoop and states the fashion of how to optimize the algorithm and the key point of implementing in details after analyzing the status quo related to this study. Estimating the complexity of the algorithm by experiments indicates the current problems and the direction for the future study.","PeriodicalId":313228,"journal":{"name":"2012 Ninth Web Information Systems and Applications Conference","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133958326","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}
Dawen Jia, Cheng Zeng, Zhiyong Peng, Peng Cheng, Zhimin Yang
Classifying Web users based on multi-dimensional features is one of the foundations of realizing personalized Web applications. It could be used for user classification model, users' multi-dimensional data analysis, potential user group discovery and personalized recommendation and so forth. In this paper, a variable granularity user classification algorithm based on Web users' multidimensional features is proposed. Given a user feature model, the algorithm will mine all common feature categories and find the relationships between them. A series of experiments are conducted to analyze the performances of this algorithm with different condition. The experimental results indicate that this algorithm has good performance and can be deployed in Web applications with massive Web users.
{"title":"A Variable Granularity User Classification Algorithm Based on Multi-dimensional Features of Users","authors":"Dawen Jia, Cheng Zeng, Zhiyong Peng, Peng Cheng, Zhimin Yang","doi":"10.1109/WISA.2012.45","DOIUrl":"https://doi.org/10.1109/WISA.2012.45","url":null,"abstract":"Classifying Web users based on multi-dimensional features is one of the foundations of realizing personalized Web applications. It could be used for user classification model, users' multi-dimensional data analysis, potential user group discovery and personalized recommendation and so forth. In this paper, a variable granularity user classification algorithm based on Web users' multidimensional features is proposed. Given a user feature model, the algorithm will mine all common feature categories and find the relationships between them. A series of experiments are conducted to analyze the performances of this algorithm with different condition. The experimental results indicate that this algorithm has good performance and can be deployed in Web applications with massive Web users.","PeriodicalId":313228,"journal":{"name":"2012 Ninth Web Information Systems and Applications Conference","volume":"117 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131248506","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}
Cloud computing provides virtualized, dynamically-scalable computing power. At the same time, reduction of cost is also considered as an important advantage of cloud computing. Data integration can notably benefit from cloud computing because integrating data is usually an expensive task. However, existing optimization techniques pay less attention on the fact that different execution plans of the same data integration application generate different usage costs while cloud computing provides good enough performance, so this paper introduces the cost optimization of cloud-based data integration system. The data integration system's data service layer facilitates accessing and composing information from a range of enterprise data sources through data service composition. In addition, two task scheduling algorithms for parallel part and non-parallel part are proposed to minimize the usage cost required to complete the execution of composite data service when computational capability provided by cloud computing is charged. Both of the two can obtain optimal plans in polynomial time. Experiments with the system indicate that our algorithms can lead to significant cost saving over more straightforward techniques.
{"title":"Cost Optimization of Cloud-Based Data Integration System","authors":"P. Zhang, Yanbo Han, Zhuofeng Zhao, Guiling Wang","doi":"10.1109/WISA.2012.13","DOIUrl":"https://doi.org/10.1109/WISA.2012.13","url":null,"abstract":"Cloud computing provides virtualized, dynamically-scalable computing power. At the same time, reduction of cost is also considered as an important advantage of cloud computing. Data integration can notably benefit from cloud computing because integrating data is usually an expensive task. However, existing optimization techniques pay less attention on the fact that different execution plans of the same data integration application generate different usage costs while cloud computing provides good enough performance, so this paper introduces the cost optimization of cloud-based data integration system. The data integration system's data service layer facilitates accessing and composing information from a range of enterprise data sources through data service composition. In addition, two task scheduling algorithms for parallel part and non-parallel part are proposed to minimize the usage cost required to complete the execution of composite data service when computational capability provided by cloud computing is charged. Both of the two can obtain optimal plans in polynomial time. Experiments with the system indicate that our algorithms can lead to significant cost saving over more straightforward techniques.","PeriodicalId":313228,"journal":{"name":"2012 Ninth Web Information Systems and Applications Conference","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129554776","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}
This paper examines the importance of non-topological node attributes for link prediction in social networks. Rank method and supervised learning method were introduced to show the role of the node attributes in link prediction respectively. A rule for choosing the appropriate node attributes was discussed and a method for aggregating two node attributes was proposed. The result of the experiments on a blog dataset showed that using non-topological node attributes make a better performance in link prediction.
{"title":"Using Non-topological Node Attributes to Improve Results of Link Prediction in Social Networks","authors":"Yu Zhang, Feng Li, Bin Xu, Kening Gao, Ge Yu","doi":"10.1109/WISA.2012.21","DOIUrl":"https://doi.org/10.1109/WISA.2012.21","url":null,"abstract":"This paper examines the importance of non-topological node attributes for link prediction in social networks. Rank method and supervised learning method were introduced to show the role of the node attributes in link prediction respectively. A rule for choosing the appropriate node attributes was discussed and a method for aggregating two node attributes was proposed. The result of the experiments on a blog dataset showed that using non-topological node attributes make a better performance in link prediction.","PeriodicalId":313228,"journal":{"name":"2012 Ninth Web Information Systems and Applications Conference","volume":"93 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126177942","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}
With the rapid growing popularity of XML to represent data, how to make good use of XML data in relational databases is worthy of study. Storing XML data as text in relational databases is a traditional strategy which cannot reflect the feature of XML format. In this paper, a mechanism for XML data storage and query in relational databases is proposed. XML data can be stored in relational tables and XQuery expressions can be evaluated as a part of SQL for XML data query. XQuery grammar tree and Query tree model for XML data query in rela-tional databases is presented to gain more efficient performance while querying XML data. Appropriative algorithm for evaluating XPath is also presented in this paper by which XQuery can be evaluated rapidly and efficiency. Finally, experiments invalidate the strategy of XML storage and run the algorithm on real XML datasets to show the efficiency compared with other mechanisms.
{"title":"Query XML Data in RDBMS","authors":"Xiangyu Hu, Xin Lian, Yunyin Mo, Haiwei Zhang, Xiaojie Yuan","doi":"10.1109/WISA.2012.12","DOIUrl":"https://doi.org/10.1109/WISA.2012.12","url":null,"abstract":"With the rapid growing popularity of XML to represent data, how to make good use of XML data in relational databases is worthy of study. Storing XML data as text in relational databases is a traditional strategy which cannot reflect the feature of XML format. In this paper, a mechanism for XML data storage and query in relational databases is proposed. XML data can be stored in relational tables and XQuery expressions can be evaluated as a part of SQL for XML data query. XQuery grammar tree and Query tree model for XML data query in rela-tional databases is presented to gain more efficient performance while querying XML data. Appropriative algorithm for evaluating XPath is also presented in this paper by which XQuery can be evaluated rapidly and efficiency. Finally, experiments invalidate the strategy of XML storage and run the algorithm on real XML datasets to show the efficiency compared with other mechanisms.","PeriodicalId":313228,"journal":{"name":"2012 Ninth Web Information Systems and Applications Conference","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121971772","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}
Security is a base on which E-government system can run very well, but the achievement of security goals relies on various financial and human resource investments during E-government system construction and maintenance. Security investment of E-government system has many characteristics, such as uncertainty, high risk, strong dependency, persistence and so on. Firstly, this paper applies SSA analysis methods to analyze the survivability of E-government system, and give survivability map, then it uses multi-attribute decision-making methods to provide security investment strategies of E-government system.
{"title":"Research on Investment Strategies of E-government System Based on the Survivability","authors":"Meng Xianghong, W. Xiaoli","doi":"10.1109/WISA.2012.16","DOIUrl":"https://doi.org/10.1109/WISA.2012.16","url":null,"abstract":"Security is a base on which E-government system can run very well, but the achievement of security goals relies on various financial and human resource investments during E-government system construction and maintenance. Security investment of E-government system has many characteristics, such as uncertainty, high risk, strong dependency, persistence and so on. Firstly, this paper applies SSA analysis methods to analyze the survivability of E-government system, and give survivability map, then it uses multi-attribute decision-making methods to provide security investment strategies of E-government system.","PeriodicalId":313228,"journal":{"name":"2012 Ninth Web Information Systems and Applications Conference","volume":"67 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126837759","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}
Chunhua Dong, Jingbing Li, Mengxing Huang, Yong Bai
When medical images transmitted and stored in hospitals, it require strict security, confidentiality and integrity. However, the transmission of wireless and wired networks has made the medical information vulnerable to attacks like tampering, hacking etc. And the ROI of medical image is unable to tolerate significant changes. In order to dealing these problems, we have proposed an algorithm that introducing the digital watermarking technology to increase the security of medical images. The scheme uses a part of sign sequence of DCT coefficients as the feature vector of images. It can avoid the sophisticated process of finding the Region of Interest (ROI) of medical images. At the same time, the watermarking image is encrypted by Logistic Map to enhance its confidentiality. The experimental results show that the scheme has strong robustness against common attacks and geometric attacks. Moreover, compared with the existing medical watermarking techniques, it can embed much more data, less complexity and make embed multi watermarks realized.
{"title":"The Medical Image Watermarking Algorithm with Encryption by DCT and Logistic","authors":"Chunhua Dong, Jingbing Li, Mengxing Huang, Yong Bai","doi":"10.1109/WISA.2012.51","DOIUrl":"https://doi.org/10.1109/WISA.2012.51","url":null,"abstract":"When medical images transmitted and stored in hospitals, it require strict security, confidentiality and integrity. However, the transmission of wireless and wired networks has made the medical information vulnerable to attacks like tampering, hacking etc. And the ROI of medical image is unable to tolerate significant changes. In order to dealing these problems, we have proposed an algorithm that introducing the digital watermarking technology to increase the security of medical images. The scheme uses a part of sign sequence of DCT coefficients as the feature vector of images. It can avoid the sophisticated process of finding the Region of Interest (ROI) of medical images. At the same time, the watermarking image is encrypted by Logistic Map to enhance its confidentiality. The experimental results show that the scheme has strong robustness against common attacks and geometric attacks. Moreover, compared with the existing medical watermarking techniques, it can embed much more data, less complexity and make embed multi watermarks realized.","PeriodicalId":313228,"journal":{"name":"2012 Ninth Web Information Systems and Applications Conference","volume":"84 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132037654","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}
Web services have been emerging and are by now one of the most popular techniques for building versatile distributed systems. With the increasing popularity of the Restful Web services on the network, how to select the real-world Restful Web services accurately from the ordinary web pages, thus increase the need for services discovering. In this paper, based on the researches of the SOAP-based Web services and Restful services, we develop a service pattern discovery system for the Restful Web services, and introduce the research on the service feature selecting and services classification.
{"title":"Towards Automatic Discovering for a Real-World RESTful Web Service","authors":"Qing Liu, Chenhe Liu, Huian Li, Xiang Xu, Lexi Gao","doi":"10.1109/WISA.2012.35","DOIUrl":"https://doi.org/10.1109/WISA.2012.35","url":null,"abstract":"Web services have been emerging and are by now one of the most popular techniques for building versatile distributed systems. With the increasing popularity of the Restful Web services on the network, how to select the real-world Restful Web services accurately from the ordinary web pages, thus increase the need for services discovering. In this paper, based on the researches of the SOAP-based Web services and Restful services, we develop a service pattern discovery system for the Restful Web services, and introduce the research on the service feature selecting and services classification.","PeriodicalId":313228,"journal":{"name":"2012 Ninth Web Information Systems and Applications Conference","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127033582","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 : 2012-11-16DOI: 10.1109/GreenCom.2012.13
Zhiming Ding, Xu Gao, Limin Guo, Qi Yang
Efficient retrieval of dynamically generated, spatial-temporal, and heterogeneous sampling data in the Internet of Things is a key challenge in recent years. However, current search engine techniques are not suitable for such kind of data. To solve this problem, we propose a Hybrid Search Engine Technique for the Internet of Things based on Spatial-Temporal, Value-based, and Keyword-based Conditions ("IoT-SVK Search Engine"), in this paper. The IoT-SVK search engine has satisfactory performances in supporting multi-modal retrieval conditions, and thus provides a good solution for real-time searching of massive sampling data in the Internet of Things.
{"title":"A Hybrid Search Engine Framework for the Internet of Things","authors":"Zhiming Ding, Xu Gao, Limin Guo, Qi Yang","doi":"10.1109/GreenCom.2012.13","DOIUrl":"https://doi.org/10.1109/GreenCom.2012.13","url":null,"abstract":"Efficient retrieval of dynamically generated, spatial-temporal, and heterogeneous sampling data in the Internet of Things is a key challenge in recent years. However, current search engine techniques are not suitable for such kind of data. To solve this problem, we propose a Hybrid Search Engine Technique for the Internet of Things based on Spatial-Temporal, Value-based, and Keyword-based Conditions (\"IoT-SVK Search Engine\"), in this paper. The IoT-SVK search engine has satisfactory performances in supporting multi-modal retrieval conditions, and thus provides a good solution for real-time searching of massive sampling data in the Internet of Things.","PeriodicalId":313228,"journal":{"name":"2012 Ninth Web Information Systems and Applications Conference","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128414857","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：