{"id":{"repo_id":"gsu","oai_identifier":"oai:digitalcommons.georgiasouthern.edu:etd-1671"},"canonical_url":"https://search.dev.ndltd.org/etd/gsu/oai:digitalcommons.georgiasouthern.edu:etd-1671","repository":{"repo_id":"gsu","name":"Georgia Southern University","base_url":"https://digitalcommons.georgiasouthern.edu/do/oai/"},"display":{"title":"Credit Rating and Assignment of Naics Codes Using Lsi Method","abstract":"The objective here is first, to improve automatic assignment of industry codes using LSI (lexical processing) by increasing the algorithm efficiency (both computationally and in term of input requirements), then quantify the lender's risk as \"distance to default\" (higher distance to default indicates default is less likely to occur), estimate the distance to default for each company and combine the results to obtain an estimate of the distance to default for each NAICS code.","abstract_html":"The objective here is first, to improve automatic assignment of industry codes using LSI (lexical processing) by increasing the algorithm efficiency (both computationally and in term of input requirements), then quantify the lender's risk as "distance to default" (higher distance to default indicates default is less likely to occur), estimate the distance to default for each company and combine the results to obtain an estimate of the distance to default for each NAICS code.","abstract_has_math":false,"creators":["Ouedraogo, Jerome"],"institution":null,"degree_name":"Master of Science in Mathematics (M.S.)","degree_level":"Thesis (open access)","degree_discipline":"Department of Mathematical Sciences","degree_department":null,"school":null,"contributors":["Charles Champ","John Barkoulas"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2011,"date_issued":"2011-12-01T08:00:00Z","date_published":"2011-12-01T08:00:00Z","updated_at":"2026-07-24T02:27:19Z","subjects":["ETD. LSI","NAICS code","Distance to default"],"languages":[],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://digitalcommons.georgiasouthern.edu/etd/671","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Charles Champ","John Barkoulas"]},{"key":"dc:creator","label":"Author","values":["Ouedraogo, Jerome"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.available","label":"Dc Date Available","values":["2013-10-17T07:00:00Z"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Department of Mathematical Sciences"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Thesis (open access)"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Master of Science in Mathematics (M.S.)"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["ETD. LSI","NAICS code","Distance to default"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://digitalcommons.georgiasouthern.edu/etd/671"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["The objective here is first, to improve automatic assignment of industry codes using LSI (lexical processing) by increasing the algorithm efficiency (both computationally and in term of input requirements), then quantify the lender's risk as \"distance to default\" (higher distance to default indicates default is less likely to occur), estimate the distance to default for each company and combine the results to obtain an estimate of the distance to default for each NAICS code."]},{"key":"dc:title","label":"Title","values":["Credit Rating and Assignment of Naics Codes Using Lsi Method"]}]}],"canonical_facts":{"dc:contributor":["Charles Champ","John Barkoulas"],"dc:creator":["Ouedraogo, Jerome"],"dc:date.available":["2013-10-17T07:00:00Z"],"dc:description.abstract":["The objective here is first, to improve automatic assignment of industry codes using LSI (lexical processing) by increasing the algorithm efficiency (both computationally and in term of input requirements), then quantify the lender's risk as \"distance to default\" (higher distance to default indicates default is less likely to occur), estimate the distance to default for each company and combine the results to obtain an estimate of the distance to default for each NAICS code."],"dc:identifier":["https://digitalcommons.georgiasouthern.edu/etd/671"],"dc:subject":["ETD. LSI","NAICS code","Distance to default"],"dc:title":["Credit Rating and Assignment of Naics Codes Using Lsi Method"],"thesis:degree_discipline":["Department of Mathematical Sciences"],"thesis:degree_level":["Thesis (open access)"],"thesis:degree_name":["Master of Science in Mathematics (M.S.)"]},"updated_at":"2026-07-24T02:27:19Z"}