The linear model of market value functions is a new method for direct marketing. Just like other methods in direct marketing, attribute reduction is very important to deal with large databases. We apply the algorithm ...
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This paper surveys and investigates the strengths and weaknesses of a number of recent approaches to advanced workflow modelling. Rather than inventing just another workflow language, we briefly describe recent workfl...
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SWENET: The Network Community for softwareengineering Education is an NSF funded project to develop curriculum modules of value to faculty member's desiring to incorporate softwareengineering concepts in new or ...
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SWENET: The Network Community for softwareengineering Education is an NSF funded project to develop curriculum modules of value to faculty member's desiring to incorporate softwareengineering concepts in new or existing courses. By design, the modules are self-contained instructional units ranging from a single lecture to approximately one week of course material; in this way, instructors can adopt, adapt, and arrange modules as appropriate to their courses. The original goal was to provide appropriate coverage at the undergraduate level for the areas defined in the softwareengineering body of knowledge. Recently the focus has shifted to the more focused softwareengineering education body of knowledge developed as part of the computing curricula-softwareengineering effort. As such, SWENET is evolving to become a repository of course modules that can support a wide range of educational approaches within the general framework defined by these bodies of knowledge.
Integrating multiple features content-based image retrieval can overcome the problems of single feature, but how to organize these features and feature representation methods is difficult in image retrieval. In this p...
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ISBN:
(纸本)078037925X
Integrating multiple features content-based image retrieval can overcome the problems of single feature, but how to organize these features and feature representation methods is difficult in image retrieval. In this paper, an automatic feature weight assignment approach based on genetic algorithm is proposed. The problem of weight assignment is firstly changed into optimization problem, and genetic algorithm is used for finding the optimization weight in order to get the best retrieval results. The experimental results show that the recall and precision of this proposed approach is better than the others' weight assignment methods. This approach is robust to various kinds of features and feature representation methods, and it can get the best feature combination for image retrieval.
As e-commerce developing rapidly, it is becoming a research focus about how to capture or find customer's behavior patterns and realize commerce intelligence by use of Web mining technology. Recommendation system ...
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ISBN:
(纸本)0769519326
As e-commerce developing rapidly, it is becoming a research focus about how to capture or find customer's behavior patterns and realize commerce intelligence by use of Web mining technology. Recommendation system in electronic commerce is one of the successful applications that are based on such mechanism. We present a new framework in recommendation system by finding customer model from business data. This framework formalizes the recommending process as knowledge representation of the customer shopping information and uncertainty knowledge inference process. In our approach, we firstly build a customer model based on Bayesian network by learning from customer shopping history data, then we present a recommendation algorithm based on probability inference in combination with the last shopping action of the customer, which can effectively and in real time generate a recommendation set of commodity.
The linear model of market value functions is a new method for direct marketing. Just like other methods in direct marketing, attribute reduction is very important to deal with large databases. We apply the algorithm ...
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ISBN:
(纸本)9780769519326
The linear model of market value functions is a new method for direct marketing. Just like other methods in direct marketing, attribute reduction is very important to deal with large databases. We apply the algorithm of attribute reduction, which is based on the combination of rough set theory with the boosting algorithm, to the linear model of market value functions. Experimental results compared with the ELSA/ANN model show that the proposed algorithms can be used effectively in the linear model of market value functions.
Modern enterprises are irreversibly dependent on large-scale, adaptive, component-based information systems whose complexity frequently exceeds current engineering capabilities for intellectual control, resulting in p...
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Genetic algorithms (GAs) are efficient non-gradient stochastic search methods. Parallel GAs are proposed to overcome the deficiencies of sequential GAs, such as low speed and aptness to locally converge. However the t...
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Genetic algorithms (GAs) are efficient non-gradient stochastic search methods. Parallel GAs are proposed to overcome the deficiencies of sequential GAs, such as low speed and aptness to locally converge. However the tremendous communication cost incurred offsets the advantages of parallel GAs. Hence reducing communication cost is the key issue of this problem. Instead of reducing the communication cost simply by compressing the size of the messages, we tackle the problem by improving the effectiveness of the schema to be disseminated. We propose a new schema migration scheme (SMS). This SMS consists of a schema extracting mechanism and a schema disseminating mechanism. This SMS is valid and requires less communication cost.
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