scholar.google.com › citations
The algorithm undergoes two phases to discover MaxWFP from the traversals on WDG. In the first phase, it adopts the weightpsilas confidence level (CL) to remove ...
The algorithm undergoes two phases to discover MaxWFP from the traversals on WDG. In the first phase, it adopts the weightpsilas confidence level (CL) to remove ...
The algorithm undergoes two phases to discover MaxWFP from the traversals on WDG. In the first phase, it adopts the weight's confi-dence level (CL) to remove ...
The algorithm undergoes two phases to discover MaxWFP from the traversals on WDG. In the first phase, it adopts the weight's confi-dence level (CL) to remove ...
Bibliographic details on Efficiently Mining Maximal Frequent Patterns from Traversals on Weighted Directed Graph Using Statistical Theory.
Based on the model, an effective algorithm, called WTMaxMiner (Weighted Traversals-based Maximal Frequent Patterns Miner), is developed to discover maximal ...
To solve the problem of mining weighted patterns with noisy weight from traversals on weighted directed graph (WDG), an effective algorithm, called SMaxWFPMiner ...
This paper proposes new algorithms to discover weighted frequent patterns from the traversals, and devise support bound paradigms for candidate generation ...
Missing: Maximal Statistical
This thesis describes research work undertaken in the field of graph-based knowledge discovery (or graph mining). The objective of the research is to ...
Fuzzy Systems and Knowledge Discovery, Fourth International ...
www.computer.org › proceedings › fskd
Efficiently Mining Maximal Frequent Patterns from Traversals on Weighted Directed Graph Using Statistical Theory pp. 586-590. Mining Condensed and Lossless�...