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.","abstract_html":"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.</p><p> 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.</p><p> 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.","abstract_has_math":false,"creators":["Lukon, Shelly Candita"],"institution":null,"degree_name":"MS","degree_level":"Immediate Access","degree_discipline":"Computational Mathematics","degree_department":null,"school":null,"contributors":["Patrick Juola","John C. Kern","Kathleen Taylor"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2006,"date_issued":"2006-01-01T08:00:00Z","date_published":"2006-01-01T08:00:00Z","updated_at":"2026-07-24T02:10:02Z","subjects":["back-of-the-book indexing","hierarchical cluster analysis","humanities computing","latent semantic analysis","singular value decomposition","word sense disambiguation"],"languages":["English"],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://dsc.duq.edu/etd/842","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Patrick Juola","John C. Kern","Kathleen Taylor"]},{"key":"dc:creator","label":"Author","values":["Lukon, Shelly Candita"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.available","label":"Dc Date Available","values":["2018-08-03T07:00:00Z"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Computational Mathematics"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Immediate Access"]},{"key":"thesis:degree_name","label":"Degree Name","values":["MS"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["back-of-the-book indexing","hierarchical cluster analysis","humanities computing","latent semantic analysis","singular value decomposition","word sense disambiguation"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["English"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://dsc.duq.edu/etd/842"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["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."]},{"key":"dc:title","label":"Title","values":["A Machine-Aided Approach to Intelligent Index Generation"]}]}],"canonical_facts":{"dc:contributor":["Patrick Juola","John C. Kern","Kathleen Taylor"],"dc:creator":["Lukon, Shelly Candita"],"dc:date.available":["2018-08-03T07:00:00Z"],"dc:description.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."],"dc:identifier":["https://dsc.duq.edu/etd/842"],"dc:language":["English"],"dc:subject":["back-of-the-book indexing","hierarchical cluster analysis","humanities computing","latent semantic analysis","singular value decomposition","word sense disambiguation"],"dc:title":["A Machine-Aided Approach to Intelligent Index Generation"],"thesis:degree_discipline":["Computational Mathematics"],"thesis:degree_level":["Immediate Access"],"thesis:degree_name":["MS"]},"updated_at":"2026-07-24T02:10:02Z"}