Efficient Mining of Top-k Breaker Emerging Subgraph Patterns from Graph Datasets

نویسندگان

  • Min Gan
  • Honghua Dai
چکیده

This paper introduces a new type of discriminative subgraph pattern called breaker emerging subgraph pattern by introducing three constraints and two new concepts: base and breaker. A breaker emerging subgraph pattern consists of three subpatterns: a constrained emerging subgraph pattern, a set of bases and a set of breakers. An efficient approach is proposed for the discovery of top-k breaker emerging subgraph patterns from graph datasets. Experimental results show that the approach is capable of efficiently discovering top-k breaker emerging subgraph patterns from given datasets, is more efficient than two previous methods for mining discriminative subgraph patterns. The discovered top-k breaker emerging subgraph patterns are more informative, more discriminative, more accurate and more compact than the minimal distinguishing subgraph patterns. The top-k breaker emerging patterns are more useful for substructure analysis, such as molecular fragment analysis.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Mining Frequent Graph Sequence Patterns Induced by Vertices

The mining of a complete set of frequent subgraphs from labeled graph data has been studied extensively. Furthermore, much attention has recently been paid to frequent pattern mining from graph sequences (dynamic graphs or evolving graphs). In this paper, we define a novel class of subgraph subsequence called an “induced subgraph subsequence” to enable efficient mining of a complete set of freq...

متن کامل

Pushing Constraints to Generate Top-K Closed Sequential Graph Patterns

In this paper, the problem of finding sequential patterns from graph databases is investigated. Two serious issues dealt in this paper are efficiency and effectiveness of mining algorithm. A huge volume of sequential patterns has been generated out of which most of them are uninteresting. The users have to go through a large number of patterns to find interesting results. In order to improve th...

متن کامل

High Fuzzy Utility Based Frequent Patterns Mining Approach for Mobile Web Services Sequences

Nowadays high fuzzy utility based pattern mining is an emerging topic in data mining. It refers to discover all patterns having a high utility meeting a user-specified minimum high utility threshold. It comprises extracting patterns which are highly accessed in mobile web service sequences. Different from the traditional fuzzy approach, high fuzzy utility mining considers not only counts of mob...

متن کامل

A Parallel Approach for Frequent Subgraph Mining in a Single Large Graph Using Spark

Frequent subgraph mining (FSM) plays an important role in graph mining, attracting a great deal of attention in many areas, such as bioinformatics, web data mining and social networks. In this paper, we propose SSIGRAM (Spark based Single Graph Mining), a Spark based parallel frequent subgraph mining algorithm in a single large graph. Aiming to approach the two computational challenges of FSM, ...

متن کامل

CoreScope: Graph Mining Using k-Core Analysis - Patterns, Anomalies and Algorithms

How do the k-core structures of real-world graphs look like? What are the common patterns and the anomalies? How can we use them for algorithm design and applications? A k-core is the maximal subgraph where all vertices have degree at least k. This concept has been applied to such diverse areas as hierarchical structure analysis, graph visualization, and graph clustering. Here, we explore perva...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2009