2017-11-01
AUTHORS ABSTRACTRare pattern mining has emerged as a compelling field of research over the years. Experimental results from literature illustrate that tree-based approaches are most efficient among the rare pattern mining techniques. Despite their significance and implication, tree-based approaches become inefficient while dealing with sparse data and data with short patterns and also suffer from the limitation of memory. In this study, an efficient rare pattern mining technique has been proposed that employs a hyper-linked data structure to overcome the shortcomings of tree data structure based approaches. The hyper-linked data structure enables dynamic adjustment of links during the mining process that reduces the space overhead and performs better with sparse datasets. More... »
PAGES467-472
Pattern Recognition and Machine Intelligence
ISBN
978-3-319-69899-1
978-3-319-69900-4
http://scigraph.springernature.com/pub.10.1007/978-3-319-69900-4_59
DOIhttp://dx.doi.org/10.1007/978-3-319-69900-4_59
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