The use of trajectory analysis on a structured SOM for behavior analysis

Date of Publication

2016

Document Type

Master's Thesis

Degree Name

Master of Science in Computer Science

College

College of Computer Studies

Department/Unit

Computer Science

Thesis Adviser

Judith J. Azcarraga

Defense Panel Chair

Nelson M. Marcos

Defense Panel Member

Judith J. Azcarraga

Abstract/Summary

Trajectory analysis is important for discovering patterns from a time series data. It involves tracking of series of occurrences that will eventually lead to a specific event. It helps in understanding the situation of a particular domain. Self- Organizing Map (SOM) is a type of a unsupervised clustering algorithm that can be used in analyzing high-dimensional data. SOM is an artificial neural network algorithm that is most commonly used for identifying clusters, analyzing and discovering patterns in an input space and detecting correlation between these features. A Structured SOM, which is a variation of a SOM, is presented which was used to analyze and visualize trajectory patterns of a given sample. In a Structured SOM, before training, some areas of the map would be preassigned to specific class labels. During the training phase, samples are restricted to select its best-matching unit among the predened labels. This research presents the use of trajectory analysis on a Structured SOM for analyzing the patterns extracted from time-series data and using these extracted patterns to predict the behavior of new samples. For the experiments of this research EEG or brainwaves signal data was used. The research made use of three different trajectory similarity measures namely: cluster similarity, structure similarity and coordinate distance for determining the best matching trajectory. Results of the different experiments shows that using any of the thee trajectory similarity measure would yield similar results.

Abstract Format

html

Language

English

Format

Electronic

Accession Number

CDTG006843

Shelf Location

Archives, The Learning Commons, 12F Henry Sy Sr. Hall

Physical Description

1 computer optical disc ; 4 3/4 in.

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