Document Type

Conference Document

Date

2005

Embargo Period

1-14-2011

Keywords

Document classification, Bag-of-words, Natural Language Processing, Support Vector Machine, One-Class algorithm

Language

English

Disciplines

Library and Information Science

Description/Abstract

Experiments were conducted to test several hypotheses on methods for improving document classification for the malicious insider threat problem within the Intelligence Community. Bag-of-words (BOW) representations of documents were compared to Natural Language Processing (NLP) based representations in both the typical and one-class classification problems using the Support Vector Machine algorithm. Results show that the NLP features significantly improved classifier performance over the BOW approach both in terms of precision and recall, while using many fewer features. The one-class algorithm using NLP features demonstrated robustness when tested on new domains.

Creative Commons License

Creative Commons License
This work is licensed under a Creative Commons Attribution 3.0 License.

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