Sequential Data Mining using Correlation Matrix Memory

TL;DR

This paper introduces a novel sequential data mining method leveraging correlation matrix memory and Logical Match to identify patterns, validated on artificial and real datasets from NCBI databank.

Contribution

The paper presents a new approach combining correlation matrix memory with Logical Match for efficient sequential data mining.

Findings

Effective pattern mining demonstrated on artificial data.

Successful application to real data from NCBI databank.

Method shows potential for accurate sequential pattern detection.

Abstract

This paper proposes a method for sequential data mining using correlation matrix memory. Here, we use the concept of the Logical Match to mine the indices of the sequential pattern. We demonstrate the uniqueness of the method with both the artificial and the real datum taken from NCBI databank.