Browsing by Author "Fahy, Conor"
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Ant colony stream clustering: A fast density clustering algorithm for dynamic data streams
Fahy, Conor; Yang, Shengxiang; Gongora, Mario Augusto (Article)A data stream is a continuously arriving sequence of data and clustering data streams requires additional considerations to traditional clustering. A stream is potentially unbounded, data points arrive on-line and each ... -
Dynamic based stream clustering using ants
Fahy, Conor; Yang, Shengxiang (Conference)Data stream mining is the process of extracting knowledge from continuous sequences of data. It differs from conventional data mining in that a stream is potentially unbounded, data points arrive online and each data point ... -
Dynamic feature selection for clustering high dimensional data streams
Fahy, Conor; Yang, Shengxiang (Article)Change in a data stream can occur at the concept level and at the feature level. Change at the feature level can occur if new, additional features appear in the stream or if the importance and relevance of a feature changes ... -
Finding and tracking multi-density clusters in an online dynamic data stream
Fahy, Conor; Yang, Shengxiang (Article)Change is one of the biggest challenges in dynamic stream mining. From a data-mining perspective, adapting and tracking change is desirable in order to understand how and why change has occurred. Clustering, a form of ... -
Finding multi-density clusters in non-stationary data streams using an ant colony with adaptive parameters
Fahy, Conor; Yang, Shengxiang; Gongora, Mario Augusto (Conference)Density based methods have been shown to be an effective approach for clustering non-stationary data streams. The number of clusters does not need to be known a priori and density methods are robust to noise and changes ... -
Learning in Dynamic Data-Streams with a Scarcity of Labels
Fahy, Conor (Thesis or dissertation / Doctoral / PhD)Analysing data in real-time is a natural and necessary progression from traditional data mining. However, real-time analysis presents additional challenges to batch-analysis; along with strict time and memory constraints, ...