With the progress of computer technology and communication technology, the national economy develops rapidly, and the information level of all walks of life is getting higher and higher. All the time, all produce huge...
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data aggregation is the process of combining multiple data points or data sets into a larger data set. Through calculation, statistics or other means, it can provide higher level datainformation, which is widely used...
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datamining can uncover valuable information from large amounts of redundant data, where association rule mining is one of the most important research element. By mining association rules, we can find connections betw...
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datamining is the science and technology of extracting information from data. This is a process of generating useful knowledge from unstructured data by using advanced algorithms. data mining can be used for many pur...
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This paper studies the implementation of logistics information system based on data mining and high-performance model. At present, the information system of logistics enterprises widely adopts the distributed system o...
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Association rules(AR) are a common data classification method. It can create more value by studying how to better mine user information and establish connections between these large number(LR) of reusable objects. For...
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This paper conducts data mining for recruitment information, and puts forward the intelligent analysis strategy of logistics information based on dynamic data miningtechnology. The new trend of change presents the ch...
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This paper proposes a classification methodology that combines neighborhood rough set feature selection with the fuzzy k-nearest neighbor algorithm. The method enhances the accuracy by integrating the fuzzy k-nearest ...
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Various information systems in libraries generate a large amount of transaction data during their operation. These data contain rich learning behavior information of learners, as well as their interests. If the intere...
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ISBN:
(纸本)9798400708305
Various information systems in libraries generate a large amount of transaction data during their operation. These data contain rich learning behavior information of learners, as well as their interests. If the interest features in these data are mined, it will be possible to achieve the goal of "birds of a feather flock together", which is helpful for clustering learning resources and mining user interest groups. Community detection technology is such a means to achieve this goal, and the research on this technology has positive significance for improving the intelligent service level of libraries. This paper first analyzes the key data for implementing community detection, which contains user's interest information. Then designs the system architecture and proposes a local community discovery algorithm based on the core-skeleton. Finally, explores the application value of virtual learning communities.
By utilizing geometric and astronomical knowledge, a model for the length of a solar shadow in relation to its geographical location and object height is established. The variations of shadow length concerning various...
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