Text, Image and Vector Graphics Based Appraisal of Contemporary Documents

We have designed a framework for content based appraisal of documents. Our motivation is to provide computer assisted support for answering several appraisal criteria according to the general appraisal guidelines in the National Archives and Record Administration (NARA) 1441 directive. The appraisal criteria led us to investigations related to (a) finding groups of PDF documents with similar content, (b) ranking documents according to their creation/ modification time and digital volume, and (c) detecting inconsistency between ranking and content within a group of related documents. The novelty of our work is in designing a methodology and a mathematical framework for document appraisals, and prototyping the framework working with text, image and vector graphics components of PDF documents. We present example results of grouping, ranking and integrity verification for groups of scientific documents about medical topics.

• Type: Conference
• Year: 2008
• Where: ICMLA
• Authors: Sang-Chul Lee, William McFadden, Peter Bajcsy
• Keywords: Appraisal Criteria, Content Based Appraisal, ICMLA 2008, Machine Learning, PDF Documents