Eguo.com, a Chinese Internet e-commerce company to offer consumers online shopping, delivery and other Internet related services, was built in April 1999. In April 2000, eguo launched the famous ldquoeguo one hourrdquo delivery service in Beijing, which means products ordered in the website will be delivered to consumers within one hour in Beijing. Now, eguo offers 30 lines of consumer products including CDs, books, tickets, electronics, groceries, pets, clothes, etc. This paper analyzes the running model of eguo comprehensively from the perspective of technology, management, capital, operation and cooperation. Based on the analysis and current development trend of e-commerce enterprises, this paper puts forward with some suggestions for eguo.
{"title":"Business to Consumer E-commerce Enterprises Analysis: A Case Study of eguo.com","authors":"Xiaohong Wang, Liwei Li, L. Tian, Jinghai Ao","doi":"10.1109/ICCTD.2009.33","DOIUrl":"https://doi.org/10.1109/ICCTD.2009.33","url":null,"abstract":"Eguo.com, a Chinese Internet e-commerce company to offer consumers online shopping, delivery and other Internet related services, was built in April 1999. In April 2000, eguo launched the famous ldquoeguo one hourrdquo delivery service in Beijing, which means products ordered in the website will be delivered to consumers within one hour in Beijing. Now, eguo offers 30 lines of consumer products including CDs, books, tickets, electronics, groceries, pets, clothes, etc. This paper analyzes the running model of eguo comprehensively from the perspective of technology, management, capital, operation and cooperation. Based on the analysis and current development trend of e-commerce enterprises, this paper puts forward with some suggestions for eguo.","PeriodicalId":218182,"journal":{"name":"2008 International Seminar on Future Information Technology and Management Engineering","volume":"77 6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128088100","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}
In order to manage the dynamic characteristics and provide theoretical foundation for modeling the grid services and services collaboration, by combining Object-Z with formal Statechart based on CREs (Concurrent Regular Expressions), this paper proposes an extension version of Object-Z language, GS-Z. As well, GS-Z extends Object-Z to enable the lifecycle management of grid service by introducing a concept of channel and a concept of life-thread. Furthermore, on the basis of GS-Z, this paper presents a framework for modeling grid services following WSRF specification. The model framework is illustrated through a case study.
{"title":"A Grid Service Model Framework Based on Object-Z and Statechart","authors":"W. Liu, Dong Xu, Zongtian Liu, Wen Zhou, Lei Lei","doi":"10.1109/FITME.2008.91","DOIUrl":"https://doi.org/10.1109/FITME.2008.91","url":null,"abstract":"In order to manage the dynamic characteristics and provide theoretical foundation for modeling the grid services and services collaboration, by combining Object-Z with formal Statechart based on CREs (Concurrent Regular Expressions), this paper proposes an extension version of Object-Z language, GS-Z. As well, GS-Z extends Object-Z to enable the lifecycle management of grid service by introducing a concept of channel and a concept of life-thread. Furthermore, on the basis of GS-Z, this paper presents a framework for modeling grid services following WSRF specification. The model framework is illustrated through a case study.","PeriodicalId":218182,"journal":{"name":"2008 International Seminar on Future Information Technology and Management Engineering","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128164658","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}
Enterprise bankruptcy forecasting is very important to manage credit risk and a lot of scholars applied themselves to study how to increase the accuracy of bankruptcy forecast which requires a powerful learning machine algorithm capable of good generalization on financial data. Therefore, classification algorithms like support vector machine (SVM) are popular for modeling and predicting corporate distress. However, making inferences and choosing appropriate responses based on incomplete, uncertainty and noisy data is challenging in financial settings particularly in bankruptcy prediction. In this paper, we propose a new approach for enterprise bankruptcy prediction, which uses a novel support vector machine and K-nearest neighbor (KNN-SVM) to remove noisy training examples. The experimental results show that the generalization performance and the accuracy of classification are improved significantly compared to that of the traditional SVM classifier, and adapt to engineering applications.
{"title":"Enterprise Bankruptcy Prediction Using Noisy-Tolerant Support Vector Machine","authors":"Zhong Gao, Meng Cui, L. Po","doi":"10.1109/FITME.2008.135","DOIUrl":"https://doi.org/10.1109/FITME.2008.135","url":null,"abstract":"Enterprise bankruptcy forecasting is very important to manage credit risk and a lot of scholars applied themselves to study how to increase the accuracy of bankruptcy forecast which requires a powerful learning machine algorithm capable of good generalization on financial data. Therefore, classification algorithms like support vector machine (SVM) are popular for modeling and predicting corporate distress. However, making inferences and choosing appropriate responses based on incomplete, uncertainty and noisy data is challenging in financial settings particularly in bankruptcy prediction. In this paper, we propose a new approach for enterprise bankruptcy prediction, which uses a novel support vector machine and K-nearest neighbor (KNN-SVM) to remove noisy training examples. The experimental results show that the generalization performance and the accuracy of classification are improved significantly compared to that of the traditional SVM classifier, and adapt to engineering applications.","PeriodicalId":218182,"journal":{"name":"2008 International Seminar on Future Information Technology and Management Engineering","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126528684","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}
Recently, spectral clustering has become one of the most popular modern clustering algorithms which are mainly applied to image segmentation. In this paper, we propose a new spectral clustering algorithm and attempt to use it for outlier detection in dataset. Our algorithm takes the number of neighborhoods shared by the objects as the similarity measure to construct a spectral graph. It can help to isolate outliers as well as construct a sparse matrix. We compare the performance of our algorithm with the k-means based clustering algorithm while using them to detect outliers. Experiment results show that the algorithm can obtain stable clusters and is efficient for identifying outliers.
{"title":"A Spectral Clustering Algorithm for Outlier Detection","authors":"Peng Yang, Biao Huang","doi":"10.1109/FITME.2008.120","DOIUrl":"https://doi.org/10.1109/FITME.2008.120","url":null,"abstract":"Recently, spectral clustering has become one of the most popular modern clustering algorithms which are mainly applied to image segmentation. In this paper, we propose a new spectral clustering algorithm and attempt to use it for outlier detection in dataset. Our algorithm takes the number of neighborhoods shared by the objects as the similarity measure to construct a spectral graph. It can help to isolate outliers as well as construct a sparse matrix. We compare the performance of our algorithm with the k-means based clustering algorithm while using them to detect outliers. Experiment results show that the algorithm can obtain stable clusters and is efficient for identifying outliers.","PeriodicalId":218182,"journal":{"name":"2008 International Seminar on Future Information Technology and Management Engineering","volume":"100 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124883332","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}
As market competition continues to intensify, more and more enterprises have empowered their own salespeople. And managers in enterprises are more concerned with the issues how they determine whether salespeople in enterprises suit to be empowered and how they evaluate salespeoplepsilas empowerment readiness. This paper establishes index system of salespeoplepsilas empowerment readiness in enterprises, uses analytic hierarchy process to determine the weight of each level index, establishes the fuzzy comprehensive evaluation model of salespeoplepsilas empowerment readiness in enterprises, finally the case study shows that it is reasonable and credible to evaluate salespeoplepsilas empowerment readiness with analytic hierarchy process and fuzzy comprehensive evaluation.
{"title":"Research on Salespeople's Empowerment Readiness Based on Fuzzy Comprehensive Evaluation","authors":"Zhengliang Xu, Y. Pei, Yong Su, Feng Xu","doi":"10.1109/FITME.2008.44","DOIUrl":"https://doi.org/10.1109/FITME.2008.44","url":null,"abstract":"As market competition continues to intensify, more and more enterprises have empowered their own salespeople. And managers in enterprises are more concerned with the issues how they determine whether salespeople in enterprises suit to be empowered and how they evaluate salespeoplepsilas empowerment readiness. This paper establishes index system of salespeoplepsilas empowerment readiness in enterprises, uses analytic hierarchy process to determine the weight of each level index, establishes the fuzzy comprehensive evaluation model of salespeoplepsilas empowerment readiness in enterprises, finally the case study shows that it is reasonable and credible to evaluate salespeoplepsilas empowerment readiness with analytic hierarchy process and fuzzy comprehensive evaluation.","PeriodicalId":218182,"journal":{"name":"2008 International Seminar on Future Information Technology and Management Engineering","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121815231","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}
In stock markets, the price is fluctuating around its average value with the time being. One of the volatilities is the variance heteroscedasticity. It is found that auto-regressive conditional heteroscedasticity (ARCH) model provides an alternative approach for the simulation of stock heteroscedasticity. In this paper, the application of ARCH and its modified models is presented for the risk analysis based on the stock index of America, Europe, China and other countries in Asia Pacific. GARCH-M model is used to test the long-term volatility self-similarity and the correlation between risk and return; TGARCH model is introduced to test the volatility leverage effect; EGARCH model is applied to verify the asymmetry heteroscedasticity of stock price fluctuation.
{"title":"Comparative Analysis of International Stock Market Volatility with ARCH Model","authors":"Jinchuan Ke, Zhe Chen, Rong Zhang","doi":"10.1109/FITME.2008.130","DOIUrl":"https://doi.org/10.1109/FITME.2008.130","url":null,"abstract":"In stock markets, the price is fluctuating around its average value with the time being. One of the volatilities is the variance heteroscedasticity. It is found that auto-regressive conditional heteroscedasticity (ARCH) model provides an alternative approach for the simulation of stock heteroscedasticity. In this paper, the application of ARCH and its modified models is presented for the risk analysis based on the stock index of America, Europe, China and other countries in Asia Pacific. GARCH-M model is used to test the long-term volatility self-similarity and the correlation between risk and return; TGARCH model is introduced to test the volatility leverage effect; EGARCH model is applied to verify the asymmetry heteroscedasticity of stock price fluctuation.","PeriodicalId":218182,"journal":{"name":"2008 International Seminar on Future Information Technology and Management Engineering","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131331116","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}
Tie Wang, Zhiguang Chen, Gaonan Wang, Jianyang Lin
To discriminate the quality on traditional Chinese medicines RADIX NOTOGINSENG real-time, according to the characters of radix notoginseng finger printer, the basic concepts of rough set are introduced briefly. For rough sets can only deal with discrete data, the discretization of data is the key factor in the rough sets applied in quality assessment, we present a method of discretization based on cluster category which combined with the characteristic of rough sets and artificial neutral network, its generalization is well. Using methods rough sets and artificial neutral network to assess radix notoginseng without any additional prior model assumption, rough sets data analysis can eliminate the redundancy of attributes and its value, identify the dependence in the attributes. We get a collective production rules about the chemical pattern classification system from sample data. When the model of chemical pattern classification is built by these rules, its meaning is very understandable in chemical domain, and the prediction of the model is also well.
{"title":"Radix Notoginseng Quality Assessment Based on Rough Sets and Neutral Network","authors":"Tie Wang, Zhiguang Chen, Gaonan Wang, Jianyang Lin","doi":"10.1109/FITME.2008.19","DOIUrl":"https://doi.org/10.1109/FITME.2008.19","url":null,"abstract":"To discriminate the quality on traditional Chinese medicines RADIX NOTOGINSENG real-time, according to the characters of radix notoginseng finger printer, the basic concepts of rough set are introduced briefly. For rough sets can only deal with discrete data, the discretization of data is the key factor in the rough sets applied in quality assessment, we present a method of discretization based on cluster category which combined with the characteristic of rough sets and artificial neutral network, its generalization is well. Using methods rough sets and artificial neutral network to assess radix notoginseng without any additional prior model assumption, rough sets data analysis can eliminate the redundancy of attributes and its value, identify the dependence in the attributes. We get a collective production rules about the chemical pattern classification system from sample data. When the model of chemical pattern classification is built by these rules, its meaning is very understandable in chemical domain, and the prediction of the model is also well.","PeriodicalId":218182,"journal":{"name":"2008 International Seminar on Future Information Technology and Management Engineering","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125544571","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 applied the data envelopment analysis and the stochastic frontier analysis based on Cobb-Douglas production function to found the model for logistics center location, studied the problem by the real data, and tested the consistency of the two methods and got the conclusion that can make comprehensive use of the DEA and the SFA to solve the problem of logistics center location (LCL).
{"title":"Research of Logistics Center Location Based on DEA and SFA","authors":"W. Tao, Li Bo, Denghua","doi":"10.1109/FITME.2008.97","DOIUrl":"https://doi.org/10.1109/FITME.2008.97","url":null,"abstract":"This paper applied the data envelopment analysis and the stochastic frontier analysis based on Cobb-Douglas production function to found the model for logistics center location, studied the problem by the real data, and tested the consistency of the two methods and got the conclusion that can make comprehensive use of the DEA and the SFA to solve the problem of logistics center location (LCL).","PeriodicalId":218182,"journal":{"name":"2008 International Seminar on Future Information Technology and Management Engineering","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133781910","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}
The asset evaluation process plays an important role in portfolio optimization because it is the prerequisite for investment decision making and directly influences on the asset allocation. This paper presents an evaluation analysis of stock investment for portfolio optimization based on data envelopment analysis (DEA) model. Considering the relationship between portfolio return and risk, the efficient DEA models and relative evaluation criteria are established. The empirical analysis is conducted on twenty-seven stocks selected from five industrial sectors of China A-share stock market, and a comparative analysis is extended for the fundamental and weight-restricted DEA models.
{"title":"Empirical Analysis of Portfolio Optimization Based on DEA Model","authors":"Jinchuan Ke, Jiao Qiao, Guang-chao Wang","doi":"10.1109/FITME.2008.129","DOIUrl":"https://doi.org/10.1109/FITME.2008.129","url":null,"abstract":"The asset evaluation process plays an important role in portfolio optimization because it is the prerequisite for investment decision making and directly influences on the asset allocation. This paper presents an evaluation analysis of stock investment for portfolio optimization based on data envelopment analysis (DEA) model. Considering the relationship between portfolio return and risk, the efficient DEA models and relative evaluation criteria are established. The empirical analysis is conducted on twenty-seven stocks selected from five industrial sectors of China A-share stock market, and a comparative analysis is extended for the fundamental and weight-restricted DEA models.","PeriodicalId":218182,"journal":{"name":"2008 International Seminar on Future Information Technology and Management Engineering","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129566109","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}
Principal components analysis (PCA) is a basic method widely used in face feature extraction and recognition. In order to overcome the shortcoming of absent consideration of the between-class information and the defect of the inconvenient update of the eigen-space in the traditional PCA method, this paper proposed a cluster-based feature projection method. The method enlarges the difference of samples in the different classes, while the difference of the same classes is reduced. Experimental results on ORL face database show that the method has higher correct recognition rate and higher recognition speeds than traditional PCA algorithm.
{"title":"Research on Face Recognition Based on PCA","authors":"Hong Duan, Ruohe Yan, Kunhui Lin","doi":"10.1109/FITME.2008.115","DOIUrl":"https://doi.org/10.1109/FITME.2008.115","url":null,"abstract":"Principal components analysis (PCA) is a basic method widely used in face feature extraction and recognition. In order to overcome the shortcoming of absent consideration of the between-class information and the defect of the inconvenient update of the eigen-space in the traditional PCA method, this paper proposed a cluster-based feature projection method. The method enlarges the difference of samples in the different classes, while the difference of the same classes is reduced. Experimental results on ORL face database show that the method has higher correct recognition rate and higher recognition speeds than traditional PCA algorithm.","PeriodicalId":218182,"journal":{"name":"2008 International Seminar on Future Information Technology and Management Engineering","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129998587","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：