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Data clustering thesis

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File s under embargo. Cite Share. For massive data analysis, the computational bottlenecks exist in two ways. Firstly, the data could be too large that it is not easy to store and read.
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Statistical Analysis of Spherical Data: Clustering, Feature Selection and Applications

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Time Series Clustering with Water Temperature Data – PProjects

Abstract:- The term Big Data is used for denoting the collection of datasets that are extremely large and complex making it difficult to process using traditional data processing applications. The datasets clustering has become a challenging issue in the field of big data. The most widely used procedure to identify clusters is known as k-means. The k-means algorithm finds clusters with the least inertia for a given k. A drawback of this k-means is that if k is not known.
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On PRIFCM algorithm for data clustering, image segmentation and comparative analysis

This thesis studies three different approaches to cluster time series data using the unsupervised pattern recognition method called hierarchical clustering. The underlying data constitute long-term water temperature measurements of several Swiss water bodies and originates from metering stations which are managed by the Federal Office for the Environment in Switzerland. The goal is to group these stations according to the resemblance of their hydrologic temperature curve over a period of ten years with a ten-minute sampling rate of detail. Stations that exhibit very similar short-term as well as long-term temperature behaviour and evolution over time should be grouped into the same clusters. These clusterings should provide a better understanding of the data heterogeneity received from the various metering stations in Switzerland and support future decisions regarding the integration of new stations.
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Selecting the right big data research topics is the first and most important step in the process of writing academic papers or essays. Big data is becoming a popular phenomenon among scholars and practitioners. The multidisciplinary background of big data research encompasses a wide spectrum that covers scientific publications in different study areas. Nevertheless, some students have difficulties choosing big data topics for their computer science thesis or research paper. To solve this problem, we list the top topics in data science that learners can choose from.
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