Defense Date
11-17-2006
Graduation Date
Fall 2006
Availability
Immediate Access
Submission Type
thesis
Degree Name
MS
Department
Computational Mathematics
School
McAnulty College and Graduate School of Liberal Arts
Committee Chair
Patrick Juola
Committee Member
John C. Kern
Committee Member
Kathleen Taylor
Keywords
back-of-the-book indexing, hierarchical cluster analysis, humanities computing, latent semantic analysis, singular value decomposition, word sense disambiguation
Abstract
Back-of-the-book indexing is the process of generating a list of relevant terms, sub-terms and cross-references from a corpus and providing the user with corresponding page references.
Several cognitive tasks are necessary to produce a good index, and are performed primarily by the human indexer. Indexing has become somewhat automated through computer applications, which at best generate a concordance, and exist to reduce the mundane portions of the process. However, none of these tools determines which terms to index, nor do they capture context-sensitive information about terms and their relationships. Human indexers perform these time-consuming tasks.
The challenge is to develop software that bridges the gap between computerized concordances and manual indexing. The prototype application described herein is unique in its ability to incorporate the intelligent portions of the process. Because of this, it provides a robust draft index that a human indexer can refine in a fraction of the time.
Format
Language
English
Recommended Citation
Lukon, S. (2006). A Machine-Aided Approach to Intelligent Index Generation (Master's thesis, Duquesne University). Retrieved from https://dsc.duq.edu/etd/842