Matrix: A Large-scale Data Mining System for Structured Data

Mining Structured Data Mining Structured Data

Mining Large-Scale Retail Data

Understanding customer buying patterns is of great interest in the retail industry. Applications include targeted advertising, optimized product placement, and cross-promotions. Association rules, expressed as A → B (if A then B) are a common and easily understandable ways to represent buying patterns. While the problem of mining such rules has received considerable attention over the past year...

Learning FCM by Data Mining in a Purchase System

Fuzzy Cognitive Maps (FCMs) have successfully been applied in numerous domains to show the relations between essential components in complex systems. In this paper, a novel learning method is proposed to construct FCMs based on historical data and by using meta-heuristic: Genetic Algorithm (GA), Simulated Annealing (SA), and Tabu Search (TS). Implementation of the proposed method has demonstrat...

A structured matrix factorization framework for large scale calcium imaging data analysis

We present a structured matrix factorization approach to analyzing calcium imaging recordings of large neuronal ensembles. Our goal is to simultaneously identify the locations of the neurons, demix spatially overlapping components, and denoise and deconvolve the spiking activity of each neuron from the slow dynamics of the calcium indicator. The matrix factorization approach relies on the obser...

A Robust System Architecture for Mining Semi-Structured Data

The value of extracting knowledge from semi-structured data is readily apparent with the explosion of the WWW and the advent of digital libraries. This paper proposes a versatile system architecture for text mining that maintains structured data components in a relational database and unstructured concepts in a concept library. After a detailed explanation of our system architecture, we briefly...