253 search results - page 13 / 51 » Using and Learning Semantics in Frequent Subgraph Mining |
83
Voted
PKDD
2010
Springer
14 years 10 months ago
2010
Springer
Pattern mining methods for graph data have largely been restricted to ground features, such as frequent or correlated subgraphs. Kazius et al. have demonstrated the use of elaborat...
SSDBM
2007
IEEE
15 years 6 months ago
2007
IEEE
We present a novel application of graph database mining to identify tertiary motifs in RNA structures. In od, we abstract an RNA molecule as a labeled graph and use a frequent sub...
104
Voted
CIDM
2009
IEEE
15 years 3 months ago
2009
IEEE
The graph classification problem is learning to classify separate, individual graphs in a graph database into two or more categories. A number of algorithms have been introduced fo...
110
Voted
ICMCS
2006
IEEE
15 years 5 months ago
2006
IEEE
For large scale automatic semantic video characterization, it is necessary to learn and model a large number of semantic concepts. These semantic concepts do not exist in isolatio...
92
Voted
ICTAI
2007
IEEE
15 years 6 months ago
2007
IEEE
The majority of text retrieval and mining techniques are still based on exact feature (e.g. words) matching and unable to incorporate text semantics. Many researchers believe that...