In this paper, we designed a customer-centered data warehouse system with five subjects： listing, bidding, transaction, accounts, and customer contact based on the business process of online auction companies. For ea...In this paper, we designed a customer-centered data warehouse system with five subjects： listing, bidding, transaction, accounts, and customer contact based on the business process of online auction companies. For each subject, we analyzed its fact indexes and dimensions. Then take transaction subject as example, analyzed the data warehouse model in detail, and got the multi-dimensional analysis structure of transaction subject. At last, using data mining to do customer segmentation, we divided customers into four types： impulse customer, prudent customer, potential customer, and ordinary customer. By the result of multi-dimensional customer data analysis, online auction companies can do more target marketing and increase customer loyalty.展开更多
A method for solving the winner determination problem （WDP） in multi-attribute procurement auctions is proposed, based on technical and business experts＇ evaluation information. Firstly, on the background of procur...A method for solving the winner determination problem （WDP） in multi-attribute procurement auctions is proposed, based on technical and business experts＇ evaluation information. Firstly, on the background of procurements in China, a multi-attribute pro- curement auction mechanism is presented, where technical and business experts participate in the bid evaluation. Then, the concept of TOPSIS is used to determine the positive and negative ideal points of the WDP according to bid prices, the technical and business experts＇ evaluation information. Further, the closeness coefficient of each bidder （candidate supplier） is obtained by calculating the distances to the positive and negative ideal points. Thus, the winning supplier can be determined according to the closeness coefficients. Finally, a numerical example is used to illustrate the use of the proposed method.展开更多
Based on the classification to the attribute information of auctioned commodity, the valuation signal of auctioned commodity is categorized into two groups: codable valuation signal and un-codable valuation signal. A ...Based on the classification to the attribute information of auctioned commodity, the valuation signal of auctioned commodity is categorized into two groups: codable valuation signal and un-codable valuation signal. A valuation signal model is developed and used to reason under the environment of common valuation auction. The results show that the value of commodity auctioned online tends to be lower and the commodity with bigger factor that can be described online is more suitable for online auction.展开更多
One of the remarkable features of the next generation network is the integration of heterogeneous wireless networks, which enables mobile users with multi-mode terminals access to the best available network seamlessly...One of the remarkable features of the next generation network is the integration of heterogeneous wireless networks, which enables mobile users with multi-mode terminals access to the best available network seamlessly. However, most of previous work only takes account of either maximizing single user＇s utility or the whole network＇s payoff, rarely considers the negotiation between them. In this paper, we propose a novel network selection approach using improved multiplicative multi-attribute auction （MMA）. At first, an improved MMA method is put forward to define the user＇s utility. Additionally, user cost is defined by considering allocated bandwidth, network load intensity and cost factor parameter. And last the best suitable network is selected according to the user＇s performance-cost-ration. Simulation results confirm that the proposed scheme outperforms the existing scheme in terms of network selection＇s fairness, user＇s performance-cost-ration, load balancing and the number of accommodated users.展开更多
The growing popularity of users in online social network gives a big opportunity for online auction.The famous Information Diffusion Mechanism(IDM)is an excellent method even meet the incentive compatibility and indiv...The growing popularity of users in online social network gives a big opportunity for online auction.The famous Information Diffusion Mechanism(IDM)is an excellent method even meet the incentive compatibility and individual rationality.Although the existing auction in online social network has considered the buyers’information which is not known by the seller,current mechanism still can not preserve the privacy information of users in online social network.In this paper,we propose a novel mechanism based on the IDM and differential privacy.Our mechanism can successfully process the auction and at the same time preserve clients’price information from neighbours.We achieved these by adding virtual nodes to each node and Laplace noise for its price in the auction process.We also formulate this mechanism on the real network and the random network,scale-free network to show the feasibility and effectiveness of the proposed mechanism.The evaluation shows that the result of our methods only depend on the noise added to the agents.It is independent from the agents’original price.展开更多
We propose a dynamically integrated regression model to predict the price of online auctions,including the final price.Different from existing models,the proposed method uses not only the historical price but also the...We propose a dynamically integrated regression model to predict the price of online auctions,including the final price.Different from existing models,the proposed method uses not only the historical price but also the information from bidding time.Consequently,the prediction accuracy is improved compared with the existing methods.An estimation method based on B-spline approximation is proposed for the estimation and the inference of parameters and nonparametric functions in this model.The minimax rate of convergence for the prediction risk and large-sample results including the consistency and the asymptotic normality are established.Simulation studies verify the finite sample performance and the appealing prediction accuracy and robustness.Finally,when we apply our method to a 7-day auction of iPhone 6s during December 2015 and March 2016,the proposed method predicts the ending price with a much smaller error than the existing models.展开更多
基金Supported by the National Natural Science Foundation of China (70471037)211 Project Foundation of Shanghai University (8011040506)
文摘In this paper, we designed a customer-centered data warehouse system with five subjects： listing, bidding, transaction, accounts, and customer contact based on the business process of online auction companies. For each subject, we analyzed its fact indexes and dimensions. Then take transaction subject as example, analyzed the data warehouse model in detail, and got the multi-dimensional analysis structure of transaction subject. At last, using data mining to do customer segmentation, we divided customers into four types： impulse customer, prudent customer, potential customer, and ordinary customer. By the result of multi-dimensional customer data analysis, online auction companies can do more target marketing and increase customer loyalty.
基金supported by the National Natural Science Foundation of China(7127105171371002+1 种基金71471032)the Fundamental Research Funds for the Central Universities,NEU,China(N140607001)
文摘A method for solving the winner determination problem （WDP） in multi-attribute procurement auctions is proposed, based on technical and business experts＇ evaluation information. Firstly, on the background of procurements in China, a multi-attribute pro- curement auction mechanism is presented, where technical and business experts participate in the bid evaluation. Then, the concept of TOPSIS is used to determine the positive and negative ideal points of the WDP according to bid prices, the technical and business experts＇ evaluation information. Further, the closeness coefficient of each bidder （candidate supplier） is obtained by calculating the distances to the positive and negative ideal points. Thus, the winning supplier can be determined according to the closeness coefficients. Finally, a numerical example is used to illustrate the use of the proposed method.
基金Supported by the National Natural Science Foundation of China (No.70371004)
文摘Based on the classification to the attribute information of auctioned commodity, the valuation signal of auctioned commodity is categorized into two groups: codable valuation signal and un-codable valuation signal. A valuation signal model is developed and used to reason under the environment of common valuation auction. The results show that the value of commodity auctioned online tends to be lower and the commodity with bigger factor that can be described online is more suitable for online auction.
基金supported by the National Natural Science Funds of China for Young Scholar (61001115)the Fundamental Research Funds for the Central Universities of China (2012RC0126,2011RC0110)
文摘One of the remarkable features of the next generation network is the integration of heterogeneous wireless networks, which enables mobile users with multi-mode terminals access to the best available network seamlessly. However, most of previous work only takes account of either maximizing single user＇s utility or the whole network＇s payoff, rarely considers the negotiation between them. In this paper, we propose a novel network selection approach using improved multiplicative multi-attribute auction （MMA）. At first, an improved MMA method is put forward to define the user＇s utility. Additionally, user cost is defined by considering allocated bandwidth, network load intensity and cost factor parameter. And last the best suitable network is selected according to the user＇s performance-cost-ration. Simulation results confirm that the proposed scheme outperforms the existing scheme in terms of network selection＇s fairness, user＇s performance-cost-ration, load balancing and the number of accommodated users.
文摘The growing popularity of users in online social network gives a big opportunity for online auction.The famous Information Diffusion Mechanism(IDM)is an excellent method even meet the incentive compatibility and individual rationality.Although the existing auction in online social network has considered the buyers’information which is not known by the seller,current mechanism still can not preserve the privacy information of users in online social network.In this paper,we propose a novel mechanism based on the IDM and differential privacy.Our mechanism can successfully process the auction and at the same time preserve clients’price information from neighbours.We achieved these by adding virtual nodes to each node and Laplace noise for its price in the auction process.We also formulate this mechanism on the real network and the random network,scale-free network to show the feasibility and effectiveness of the proposed mechanism.The evaluation shows that the result of our methods only depend on the noise added to the agents.It is independent from the agents’original price.
基金supported by National Natural Science Foundation of China(Grant Nos.11528102 and 11571282)Fundamental Research Funds for the Central Universities of China(Grant Nos.JBK120509 and 14TD0046)supported by the National Science Foundation of USA(Grant No.DMS-1620898)。
文摘We propose a dynamically integrated regression model to predict the price of online auctions,including the final price.Different from existing models,the proposed method uses not only the historical price but also the information from bidding time.Consequently,the prediction accuracy is improved compared with the existing methods.An estimation method based on B-spline approximation is proposed for the estimation and the inference of parameters and nonparametric functions in this model.The minimax rate of convergence for the prediction risk and large-sample results including the consistency and the asymptotic normality are established.Simulation studies verify the finite sample performance and the appealing prediction accuracy and robustness.Finally,when we apply our method to a 7-day auction of iPhone 6s during December 2015 and March 2016,the proposed method predicts the ending price with a much smaller error than the existing models.
