Lin Cai, Xiaojun Jing, Songlin Sun, Hai Huang, Na Chen, Yueming Lu
{"title":"P2P traffic identification based on transfer learning","authors":"Lin Cai, Xiaojun Jing, Songlin Sun, Hai Huang, Na Chen, Yueming Lu","doi":"10.1109/GrC.2013.6740374","DOIUrl":"https://doi.org/10.1109/GrC.2013.6740374","url":null,"abstract":"With the rapid development of Internet, a large number of peer networks (Peer-to-Peer) applications rise and are widely used. Because of this, it is more difficult for network operators to manage and monitor their networks in a proper way. To identify the peer networks applications generating the traffic traveling through networks is necessary and if we can identify them sooner, we control them better. In this work, we use the machine learning-based classification method to identify the classes of the flows. According to previous work, we choose transfer learning algorithm to classify the traffic, and improve classified results. Finally we compare and evaluate the classification results in terms of the two metrics such as true positive ratio and time expense. Our experiments show that the machine learning algorithm is an efficient algorithm for traffic identification and is able to build a quick identification system.","PeriodicalId":415445,"journal":{"name":"2013 IEEE International Conference on Granular Computing (GrC)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122942514","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}
{"title":"Dynamic relationship between real estate prices and inflation rate","authors":"Huang Ting, Liu Huangjin","doi":"10.1109/GrC.2013.6740398","DOIUrl":"https://doi.org/10.1109/GrC.2013.6740398","url":null,"abstract":"This thesis studies the dynamic relationship between China's real estate prices and inflation rate by examining the relationship between the Consumer Price Index and Nanjing housing sales price index, to use cointegration test, the VEC model and Granger causality test, the results show that both indices are Granger causality to each other, and there is a long-term stable cointegration relationship between them. At the same time, no significant volatility spillover effects between house prices and inflation rate are found by using GARCH model to volatilities of both indices. Finally, we choose the Impulse Response Function and get the conclusion that the impact between house prices and inflation rate is asymmetric, and is not obvious in the short term but significant in the long term. By the main conclusions of the above analysis, we give some useful recommendations and countermeasures in order to provide the theoretical basis for investors and decisionmakers to make decisions.","PeriodicalId":415445,"journal":{"name":"2013 IEEE International Conference on Granular Computing (GrC)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121150904","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}
{"title":"An ad-hoc clustering algorithm based on ant colony algorithm","authors":"Ying-Wei Chen, Xin Xia, Rongxi Wang","doi":"10.1109/GrC.2013.6740382","DOIUrl":"https://doi.org/10.1109/GrC.2013.6740382","url":null,"abstract":"This paper proposes a new Ad Hoc clustering algorithm based on ant colony algorithm. The protocol has introduced the node reliability to reflect the node communication environment situation and how busy the node is. At the same time, the node reliability is one of the node pheromone factors. In the process of clustering and cluster maintenance, it elects the optimal node as cluster head to management cluster members with the guidance of the node pheromone which is cumulative and updating timely to increase the stability of the clusters formed. The clusters are based on multi-hop which can be adjusted according to the size of network. In the cluster, the cluster heads found the best route to the destination node on-demand with ant colony algorithm to reduce the burden on the cluster head and the routing overhead.","PeriodicalId":415445,"journal":{"name":"2013 IEEE International Conference on Granular Computing (GrC)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114261105","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}
{"title":"Construct rough approximation based on GAE","authors":"Lin Shi, Jun Meng, Yang Zhou, Tsauyoung Lin","doi":"10.1109/GrC.2013.6740418","DOIUrl":"https://doi.org/10.1109/GrC.2013.6740418","url":null,"abstract":"Recently cloud computing has emerged as a new paradigm which focuses on web-scale problems, large data centers, multiple models of computing and highly-interactive web applications. It is high available and scalable for distributed and parallel data storage and computing based on a large amount of cheap PCs. As the representative product, Google app engine (GAE), which acts a platform as a service (PaaS) cloud computing platform, mainly contains Google File System (GFS) and MapReduce programming model for massive data process. This paper analyses GAE from the point of Granular computing (GrC) and explain why it is suitable for massive data mining. Further we present an example of how to use it to construct neighborhoods of rough set and compute lower and upper approximations accurately and strictly.","PeriodicalId":415445,"journal":{"name":"2013 IEEE International Conference on Granular Computing (GrC)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122697486","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}
{"title":"Variable precision neighborhood rough sets on two universes","authors":"Kai Zeng, Kun She","doi":"10.1109/GrC.2013.6740447","DOIUrl":"https://doi.org/10.1109/GrC.2013.6740447","url":null,"abstract":"The theory of rough sets on two universes has brought the attention by many scholars in recent years. In this paper, we propose the variable precision neighborhood rough sets model on two universes. Furthermore, the properties of this model are studied. Finally, we investigate the uncertainty measures and give a test example.","PeriodicalId":415445,"journal":{"name":"2013 IEEE International Conference on Granular Computing (GrC)","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132000253","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}
{"title":"Research on simulation of the networks information ecological chain evolutionary process in complex network perspective","authors":"Li Beiwei, Fu Jinxin","doi":"10.1109/GrC.2013.6740404","DOIUrl":"https://doi.org/10.1109/GrC.2013.6740404","url":null,"abstract":"Based on the complex network theory, this paper defined the connotation of networks information ecological chain, and analyzed the evolution process of it. Then the evolution process of the networks information Ecological Chain is divided into four stages: formative stage, growth stage, mature stage, recession or update stage, and simulated the evolution process of the networks information Ecological Chain by the theory and means of complex network. The aim of the paper is to provide references for the follow-up study of networks information ecological chain.","PeriodicalId":415445,"journal":{"name":"2013 IEEE International Conference on Granular Computing (GrC)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115205421","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}
{"title":"Higher order vagueness and rough sets","authors":"H. Fu","doi":"10.1109/GrC.2013.6740390","DOIUrl":"https://doi.org/10.1109/GrC.2013.6740390","url":null,"abstract":"It is well-known the naive approach to consider the main flaw to vague terms is that there are no sharp boundaries between positive and negative extensions, i.e., some borderline cases exist if the predicates are vague. However, Z. Pawlak has proposed a prominent approach to vagueness based on rough set theory but it seemed to be implausible due to the boundary region as the theory constructed must be precise (or “crisp”) but not vague in some sense. On the basis of Pawlak's creative idea and efforts, A. Skowron and R. Swiniarski proceeded to examine some further problems, one of them is the problem of higher order vagueness which is exactly to say that there is not only no sharp boundary between positive and negative extensions but also no sharp boundaries between positive extension and borderline cases or between borderline cases and negative extension, etc. And the main idea of the theory was within adaptive learning framework. Contrast to their approach, I aim to provide some supplied principles in this paper to show that the problem of higher order vagueness ipso facto can be assimilated by the revised rough set theory from a philosophical point of view.","PeriodicalId":415445,"journal":{"name":"2013 IEEE International Conference on Granular Computing (GrC)","volume":"105 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115532997","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}
W. Hsieh, B. Xue, Ju-Chin Chen, K. W. Lin, Weng-Long Chang
{"title":"Clothes style recommendation system","authors":"W. Hsieh, B. Xue, Ju-Chin Chen, K. W. Lin, Weng-Long Chang","doi":"10.1109/GrC.2013.6740395","DOIUrl":"https://doi.org/10.1109/GrC.2013.6740395","url":null,"abstract":"We propose a clothes style recommendation system by analyzing the relation between facial features and clothes style. Five different kinds of face shapes and seven different kinds of clothes styles are defined in our work. To extract features that are stable under different lighting conditions, geometric information is used, which measure distance between regular features, e.g. distance between eyes, average distance from eye to nose. Instead of detecting regular facial features directly, facial feature points are detected by active shape model in advance. Then 14 different kinds of geometric information are extracted, which can capture discriminant features to describe the significance properties not only for the specific facial shape but between different facial shapes. Finally, multi-label classification is applied because one facial shape is suitable to more one clothes styles. Binary-Relevance (BP) and Label Powerset (LP) methods are used to transfer multi-label classification into multiple binary class problems and one multi-class problem, respectively. Experiments are designed to evaluate the system performance with two transferring methods, and Hamming-loss function and F-score are used for accuracy measure.","PeriodicalId":415445,"journal":{"name":"2013 IEEE International Conference on Granular Computing (GrC)","volume":"202 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114558395","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}
{"title":"A study on the relationship mechanism between institutionalized management and employee satisfaction in hotel companies","authors":"Xiaolong Tao, Wanqing Lv, Qiaoran Wang","doi":"10.1109/GrC.2013.6740424","DOIUrl":"https://doi.org/10.1109/GrC.2013.6740424","url":null,"abstract":"Improving employee satisfaction is the key to building competitive advantages in hotel companies, while strengthening institutionalized management of hotels is conducive to improving employee satisfaction. A deep analysis of the relationship mechanism between institutionalized management and employee satisfaction will be of great value for hotel companies in seeking out effective measures to improve employee satisfaction. Starting from raising the level of institutionalized management of hotel enterprises, this paper constructs a theoretic model of the relationship among institutionalized management, management behavior, organizational culture and employee satisfaction. Based on the structural equation model, the empirical research indicates that institutionalized management in hotel companies has positive correlations with standardization of internal management behavior, construction of organizational culture and employee satisfaction. It also indicates that both standardization of management behavior and the construction of organizational culture have positive correlations with employee satisfaction. Consequently, hotel companies should strengthen institutionalized management so as to improve employee satisfaction and build competitive advantages.","PeriodicalId":415445,"journal":{"name":"2013 IEEE International Conference on Granular Computing (GrC)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122662087","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}
{"title":"Parallel mining frequent patterns over big transactional data in extended mapreduce","authors":"Hui Chen, T. Lin, Zhibing Zhang, Jie Zhong","doi":"10.1109/GrC.2013.6740378","DOIUrl":"https://doi.org/10.1109/GrC.2013.6740378","url":null,"abstract":"In big data era, data size has raised from TB-level to PB-level. Traditional algorithm can not satisfy the needs of big data computing. This paper design a parallel algorithm for mining frequent pattern over big transactional data based on an extended MapReduce Frame. In which, the mass data file is firstly split into many data subfiles, the patterns in each subfile can be quickly located based on bitmap computation by scanning the data only once. And the computing results of all subfiles are merged for mining the frequent patterns in the whole big data. In order to improve the performance of the proposed method, the insignificant patterns are pruned by a statistic analysis method when the data subfiles are processed. The experimental results show that the method is efficient, strong in scalability, and can be used to efficiently mine frequent patterns in big data.","PeriodicalId":415445,"journal":{"name":"2013 IEEE International Conference on Granular Computing (GrC)","volume":"85 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124990934","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}