Efficient Mining for Structurally Diverse Subgraph Patterns in Large Molecular Databases

Machine Learning - Netherlands
doi 10.1007/s10994-010-5187-6
Full Text
Abstract

Available in full text

Date
Authors
Publisher

Springer Science and Business Media LLC

Related search

Mining Closed Sequential Patterns in Large Sequence Databases

International Journal of Database Management Systems
2015English

Mining Frequent Subgraph Patterns From Uncertain Graphs

Ruan Jian Xue Bao/Journal of Software
Software
2009English

Mining Viewpoint Patterns in Image Databases

2003English

Incremental Frequent Subgraph Mining on Large Evolving Graphs

IEEE Transactions on Knowledge and Data Engineering
Computational TheoryComputer Science ApplicationsInformation SystemsMathematics
2017English

Efficiently Mining Long Patterns From Databases

SIGMOD Record
Information SystemsSoftware
1998English

Mining Topological Relationship Patterns From Spatiotemporal Databases

International Journal of Data Mining & Knowledge Management Process
2012English

Efficient Subgraph Matching on Large RDF Graphs Using MapReduce

Data Science and Engineering
Computational MechanicsComputer Science Applications
2019English

Mining Top-K Closed Sequential Patterns in Sequential Databases

IOSR Journal of Computer Engineering
2013English

Constraint-Based Rule Mining in Large, Dense Databases

1999English

Amanote Research

Note-taking for researchers

Follow Amanote

© 2024 Amaplex Software S.P.R.L. All rights reserved.

Privacy PolicyRefund Policy