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- W2384751446 abstract "Cloud computing contains a huge amount of data, which are featured as being widely distributed, heterogeneous, and dynamic. Thus, aiming at how to mine useful parts in these information, this paper proposes an Apriori algorithm based on cloud computing and introduces cost-sensitive learning and non-filter matrix to find k frequency set and uses the method of generating association rules to improve effectiveness of data mining. Simulation experiments show that mining algorithm in this paper is highly effective and suitable for data mining in the context of cloud computing. With the emergence of the concept cloud computing, more and more information is shared and spread through the Internet. How can carry out data mining in cloud computing became an important means of access to information (1). Literature (2) data mining solutions in the cloud computing environment is proposed, through the cloud computing and cloud computing services, describes the problem solving mechanism for data mining services. Literature (3) proposed a data processing method based on cloud computing, based on mining user browsing preference path. Experiments show that the mining algorithm for large amount of data logs, accuracy and efficiency than ordinary users preferred path mining algorithm based on frequency increased. Literature (4) proposed a new framework for data mining in the field of cloud platforms and cloud computing environments are described mechanism of data mining in the field of service-oriented. Literature (5) is a method of data mining based on cloud computing technology: large data sets and mining tasks on multiple computers in parallel, experiments show that use cloud computing technology to handle large data sets in a cluster, you can significantly improve the efficiency of data mining. Literature (6) for cloud computing resources prediction model based on data mining technology, results showed that this model not only improves the prediction accuracy of cloud computing resources, and reduce the complexity of modeling, improves the efficiency of models, to cloud computing resources provides a new way of building models. Literature (7) proposed data mining services view, cloud services task force has analyzed data mining advantages and challenges, data mining and prediction of cloud point data mining development trend of cloud services, providing data mining services framework for cloud services. This paper proposes an Apriori algorithm based on cloud computing and introduces cost-sensitive learning and non-filter matrix to find k" @default.
- W2384751446 created "2016-06-24" @default.
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- W2384751446 date "2016-04-30" @default.
- W2384751446 modified "2023-09-24" @default.
- W2384751446 title "Research of Data-Aiming Mining Algorithm in Cloud Environment" @default.
- W2384751446 doi "https://doi.org/10.14257/ijgdc.2016.9.4.08" @default.
- W2384751446 hasPublicationYear "2016" @default.
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