UGMINE: utility-based graph mining
Frequent pattern mining extracts most frequent patterns from databases. These frequency-
based frameworks have limitations in representing users' interest in many cases. In business …
based frameworks have limitations in representing users' interest in many cases. In business …
Mining weighted subgraphs in a single large graph
Weighted single large graphs are often used to simulate complex systems, and thus mining
frequent subgraphs in a weighted large graph is an important issue that has attracted the …
frequent subgraphs in a weighted large graph is an important issue that has attracted the …
Graph theory at the service of electroencephalograms
ND Iakovidou - Brain Connectivity, 2017 - liebertpub.com
The brain is one of the largest and most complex organs in the human body and EEG is a
noninvasive electrophysiological monitoring method that is used to record the electrical …
noninvasive electrophysiological monitoring method that is used to record the electrical …
Top-k interesting subgraph discovery in information networks
In the real world, various systems can be modeled using heterogeneous networks which
consist of entities of different types. Many problems on such networks can be mapped to an …
consist of entities of different types. Many problems on such networks can be mapped to an …
OWGraMi: Efficient method for mining weighted subgraphs in a single graph
Recently, the problem of mining weighted subgraphs from a weighted single graph has
become a vital issue because weighted graphs are generally used to restore, simulate or …
become a vital issue because weighted graphs are generally used to restore, simulate or …
HUSM: High utility subgraph mining in single graph databases
Z Chen, C He, G Chen, W Gan, P Fournier-Viger - Information Sciences, 2024 - Elsevier
Frequent subgraph mining (FSM) is a crucial research area with diverse applications.
However, traditional FSM treats all subgraphs as equally important. In practical applications …
However, traditional FSM treats all subgraphs as equally important. In practical applications …
WFSM-MaxPWS: an efficient approach for mining weighted frequent subgraphs from edge-weighted graph databases
Weighted frequent subgraph mining comes with an inherent challenge—namely, weighted
support does not support the downward closure property, which is often used in mining …
support does not support the downward closure property, which is often used in mining …
Mining patterns in graphs with multiple weights
Graph pattern mining aims at identifying structures that appear frequently in large graphs,
under the assumption that frequency signifies importance. In real life, there are many graphs …
under the assumption that frequency signifies importance. In real life, there are many graphs …
Beyond Frequencies: Graph Pattern Mining in Multi-weighted Graphs.
Graph pattern mining aims at identifying structures that appear frequently in large graphs,
under the assumption that frequency signies importance. Several measures of frequency …
under the assumption that frequency signies importance. Several measures of frequency …
Mining high utility subgraphs
High utility pattern mining discovers more realistic and important knowledge than the
traditional frequent pattern mining by considering non-binary occurrences of items inside …
traditional frequent pattern mining by considering non-binary occurrences of items inside …