Aug 11, 2020 · Social network trends are discovered using the A-RAFF framework as frequent subgraph patterns. A-RAFF framework is implemented in the Java ...
Nov 1, 2020 · Frequent subgraph mining have extremely high computational complexity. Finding subgraph patterns for frequently reappearing social network graph ...
In this paper we introduces a novel FSgM approach, called gSpan (Graph Based Substructure Pattern Mining) [3] to identify the frequently occurring pattern ...
A novel FSM approach, called A-RAFF (ARAnked Frequent pattern-growth Framework), to discovering and comparing the frequent pattern trends exist in the ...
Sep 8, 2020 · Saif ur Rehman , Sohail Asghar: Online social network trend discovery using frequent subgraph mining. Soc. Netw. Anal. Min. 10(1): 67 (2020).
Dec 1, 2020 · Frequent subgraph mining (FSM) plays a very significant role in graph mining, attracting a great deal of attention in different domains, such as ...
Online social network trend discovery using frequent subgraph mining. https://doi.org/10.1007/s13278-020-00682-3. Journal: Social Network Analysis and Mining ...
It allows to process, analyze, and discover significant knowledge from graph data. In graph mining, one of the most challenging tasks is frequent subgraph ...
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Sep 12, 2020 · The technique combines the notion of a group-by operation on a graph and the notion of subjective interestingness, resulting in an automated ...
Online social network trend discovery using frequent subgraph mining. Article 11 August 2020. Superimposing Periodic Subgraph Mining in Dynamic Social Network.