Outlier Mining Methods Based on Graph Structure Analysis

The Spatial Outlier Mining Algorithm based on the KNN Graph

In order to solve the defect in the spatial outlier mining algorithm that the spatial objects may be affected by their surrounding abnormal neighbors, a Based K-Nearest Neighbor (BKNN) algorithm was proposed based on the working principle of KNN Graph, which could effectively identify the spatial outliers by using cutting edge strategies. The core idea of BKNN is to calculate the dissimilarity ...

Outlier Detection using Graph Mining

Graph Mining and Outlier Detection Meet Logic Proof Tutoring

We introduce a new method for analysis and evaluation of logic proofs constructed by undergraduate students, e.g. resolution or tableaux proofs. This method employs graph mining and outlier detection. The data has been obtained from a web-based system for input of logic proofs built at FI MU. The data contains a tree structure of the proof and also temporal information about all actions that a ...

A General Variance-based Outlier Mining Model

To solve the outlier mining problems where the outliers are highly intermixed with normal data, a general Variance-based Outlier Mining Model (VOMM) is presented, in which the information of data is decomposed into normal and abnormal components according to their variances. With minimal loss of normal information in our model, outliers are viewed as the top k samples holding maximal abnormal i...

An outlier mining algorithm based on constrained concept lattice

An Outlier Mining Algorithm Based on Constrained Concept Lattice Jifu Zhang , Sulan Zhang , Kai H. Chang b, and Xiao Qin a School of Computer Science and Technology, Taiyuan University of Science and Technology, Taiyuan, P. R. China 030024 b Department of Computer Science and Software Engineering, Auburn University, Auburn, AL, USA 36849-5347 [email protected] Abstract: Traditional outlier min...