A Survey of Uncertain Data Algorithms and Applications

C.C. Aggarwal, P.S. Yu
<span title="">2009</span> <i title="Institute of Electrical and Electronics Engineers (IEEE)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/ht3yl6qfebhwrg7vrxkz4gxv3q" style="color: black;">IEEE Transactions on Knowledge and Data Engineering</a> </i> &nbsp;
In recent years, a number of indirect data collection methodologies have led to the proliferation of uncertain data. Such databases are much more complex because of the additional challenges of representing the probabilistic information. In this paper, we provide a survey of uncertain data mining and management applications. We will explore the various models utilized for uncertain data representation. In the field of uncertain data management, we will examine traditional database management
more &raquo; ... hods such as join processing, query processing, selectivity estimation, OLAP queries, and indexing. In the field of uncertain data mining, we will examine traditional mining problems such as frequent pattern mining, outlier detection, classification, and clustering. We discuss different methodologies to process and mine uncertain data in a variety of forms. Index Terms-Mining methods and algorithms, database applications, database management, information technology and systems.
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/tkde.2008.190">doi:10.1109/tkde.2008.190</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/7htcj7pcqnholig7v2ledsdqom">fatcat:7htcj7pcqnholig7v2ledsdqom</a> </span>
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