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Given the soaring amount of data being generated daily, graph mining tasks are becoming increasingly challenging, leading to tremendous demand for summarization techniques. Feature selection is a representative approach that simplifies a dataset by choosing features that are relevant to a specific task, such as classification, prediction, and anomaly detection. Although it can be viewed as a way to...
As a kind of popular problem in machine learning, multi-instance task has been researched by means of many classical methods, such as kNN, SVM, etc. For kNN classification, its performance on traditional task can be boosted by metric learning, which seeks for a data-dependent metric to make similar examples closer and separate dissimilar examples by a margin. It is a challenge to define distance between...
Malware data are typically depicted with extremely high-dimensional features, which lays an excessive computational burden on detection methods. For the sake of effectiveness and efficiency, feature selection is an indispensable part for malware detection. In this paper, we propose an ensemble feature selection method with integration of discriminative and representative properties for malware detection...
The problem of service composition with end-to-end QoS constraints has been proven to be an NP-hard problem and various evolutionary algorithms have been successfully applied to look for approximately optimal solutions within limited computation time. Favorable heuristic rules are considered as the key of such algorithms, and historical service usage data are widely utilized to help identify the distinct...
How to explore complex data? Often, several representations for each data object are available, the data are described by attributes of heterogeneous data type and/or each data object is characterized by many features. It is difficult to choose a suitable similarity measure and an appropriate data mining technique to get an unbiased overview on the information contained in complex data. In this paper,...
Whenever a research scholar starts working on some innovative ideas he/she searches for the domain specific technical research articles published as research papers in most of the international journals, conferences or workshops. The problems associated with these papers are similarity in contents and repeated relevant information. Reading these all relatedpapers completely one by one to get the latest...
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