Automatic Document Classification in Small Environments

<p>Document classification is used to sort and label documents. This gives users quicker access to relevant data. Users that work with large inflow of documents spend time filing and categorizing them to allow for easier procurement. The Automatic Classification and Document Filing (ACDF) system proposed here is designed to allow users working with files or documents to rely on the system to classify and store them with little manual attention. By using a system built on Hidden Markov Models, the documents in a smaller desktop environment are categorized with better results than the traditional Naive Bayes implementation of classification.</p>

Name thesis:degree_name

MS in Computer Science

Discipline thesis:degree_discipline

Computer Science

Year dc:date.available

2012

Author dc:creator

• McElroy, Jonathan David

Contributors dc:contributor

• Franz Kurfess

• Text Classification
• Hidden Markov Models
• Document Classification
• Automated Learning
• Databases and Information Systems

Identifier

10.15368/theses.2012.1

OAI identifier oai:identifier

oai:digitalcommons.calpoly.edu:theses-1723