The book chapters discuss Deep Learning for Clustering, Blockchain data clustering, Cybersecurity applications such as insider threat detection, scalable distributed clustering methods for massive volumes of dat
Big Data analytics are recently coming up as prominent research area in the field of data science. Apache Spark is an open source distributed data processing platform that uses distributed memory...doi:10.1007/978-3-319-74690-6_41Omar Hesham Mohamed...
The weighted possibilistic c-means algorithm is an important soft clustering technique for big data analytics with cloud computing. However, the private data will be disclosed when the raw data is directly uploaded to cloud for efficient clustering. In this paper, a secure weighted possibilistic c-...
The algorithmic methods for clustering are simple. One of the most popular clustering algorithms is thek-means algorithm, which assigns any number of data objects to one ofkclusters.107The numberkof clusters is provided by the user. The algorithm is easy to describe and to understand, but the...
Decreasing the execution time of jobs is the main motivation of clustering methods. Therefore, the purpose of this paper is to present a new method based on clustering for big data processing in Hadoop framework using the MapReduce programming model. We use the MR-DBSCAN-KD method as it is ...
In Proceedings of the IJCAI-99 Workshop on Neural, Symbolic and Reinforcement Learning Methods for Sequence Learning (pp. 17–21). Ormerod, P., & Mounfield, C. (2000). Localised structures in the temporal evolution of asset prices. In New Approaches to Financial Economics. Santa Fe ...
Electric load forecasting is crucial in the planning and operating electric power companies. It has evolved from statistical methods to artificial intelligence-based techniques that use machine learning models. In this study, we investigate short-term lo
Third, the preprocessing and cleaning aspect of dealing with data-driven models in general, and time series data in particular. All these factors led us to create a framework instead of just a model with default parameters. The framework covers the preprocessing stage, the numerous methods of ...
Anand S, Padmanabham P, Govardhan A, Kulkarni RH (2018) An extensive review on data mining methods and clustering models for intelligent transportation system. J Intell Syst 27:263–273 Google Scholar Andreopoulos B, An A, Wang X, Schroeder M (2009) A roadmap of clustering algorithms: fin...
Since 2010 he is director of the Master Business Intelligence and Big Data Analytics provided by University of Milan Bicocca. Since October 2018 he is the Head of the Statistical and Quantitative Methods Department. Carlo Zaniolo is a professor Computer Science at the University of California at ...