An automatic code classification system by using memory-based learning and information retrieval technique

Heui Seok Lim, Won Kyu Hoon Lee, Hyeon Chul Kim, Soon Young Jeong, Heon Chang Yu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper proposes an automatic code classification for Korean census data by using information retrieval technique and memoory-based learning technique. The purpose of the proposed system is to convert natural language responses on survey questionnaires into corresponding numeric codes according to standard code: book from the Census Bureau. The system was trained by memory baised learning and experimented with 46,762 industry records and occupation 36,286 records. It was evaluated by using 10-fold cross-validation method. As experimental results, the proposed system showed 99.10% and 92.88% production rates for level 2 and level 5 codes respectively.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pages577-582
Number of pages6
DOIs
Publication statusPublished - 2005
Event2nd Asia Information Retrieval Symposium, AIRS 2005 - Jeju Island, Korea, Republic of
Duration: 2005 Oct 132005 Oct 15

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume3689 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other2nd Asia Information Retrieval Symposium, AIRS 2005
Country/TerritoryKorea, Republic of
CityJeju Island
Period05/10/1305/10/15

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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