Now showing items 1-3 of 3
Edge-based mining of frequent subgraphs from graph streams
In the current era of Big data, high volumes of valuable data can be generated at a high velocity from high-varieties of data sources in various real-life applications ranging from sensor networks to social networks, from ...
Approximation to expected support of frequent itemsets in mining probabilistic sets of uncertain data
Knowledge discovery and data mining generally discovers implicit, previously unknown, and useful knowledge from data. As one of the popular knowledge discovery and data mining tasks, frequent itemset mining, in particular, ...
Frequent subgraph mining from streams of linked graph structured data
(CEUR Workshop Proceedings, 2015)
Nowadays, high volumes of high-value data (e.g., semantic web data) can be generated and published at a high velocity. A collection of these data can be viewed as a big, interlinked, dynamic graph structure of linked ...