Skip to search formSkip to main contentSkip to account menu

Structure mining

Known as: Structured data mining, Tree mining, Graph mining 
Structure mining or structured data mining is the process of finding and extracting useful information from semi-structured data sets. Graph mining… 
Wikipedia (opens in a new tab)

Related topics

Related topics

15 relations
Artificial neural networkGraph kernelID3 algorithmInductive programming

Broader (1)

Data mining

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
2016
2016
On Competition for Undergraduate Co-op Placements: A Graph Mining Approach
We propose a graph mining methodology to analyze the relationships among academic programs from the point of view of co-operative… 
Highly Cited
2013
Highly Cited
2013
Polonium: Tera-Scale Graph Mining for Malware Detection
We present Polonium, a scalable and e↵ective technology for detecting malware. We evaluated it with the largest anonymized file… 
2012
2012
A Novel Detection Approach for Cardio-Respiratory Disorders Using PPG Signals
The aim of the study was to determine the use of Photoplethysmography (PPG) as a tool for identifying cardiac and respiratory… 
2010
2010
Developing Multi-Database Mining Applications
Multi-database mining has been recognized recently as an important and strategically essential area of research in data mining… 
Highly Cited
2008
Highly Cited
2008
ORIGAMI: A Novel and Effective Approach for Mining Representative Orthogonal Graph Patterns
In this paper, we introduce the concept of α‐orthogonal patterns to mine a representative set of graph patterns. Intuitively, two… 
2008
2008
Zinc proteomics and the annotation of the human zinc proteome
Abstract Sequence databases can be searched for homologies of zinc coordination motifs with characteristic ligand signatures… 
2006
2006
From Data Mining to Behavior Mining
Knowledge economy requires data mining be more goal-oriented so that more tangible results can be produced. This requirement… 
2004
2004
Exceptional Patterns in Multi-database Mining 19 Identifying Global Exceptional Patterns in Multi-database Mining
In multi-database mining, there can be many local patterns (frequent itemsets or association rules) in each database. At the end… 
1998
1998
Efficient Mining of Association Rules in Large Dynamic Databases
Mining for association rules between items in a large database of sales transactions is an important database mining problem… 
1994
1994
Rough Set Based Classiication Methods and Extended Decision Tables
In a practical sense, database mining applications involve semi-automatic data analysis methods that help users to discover some… 
By clicking accept or continuing to use the site, you agree to the terms outlined in our Privacy Policy (opens in a new tab), Terms of Service (opens in a new tab), and Dataset License (opens in a new tab)