@inproceedings{d4261a739ba9452da39779622f2b5a9a,
title = "An automatic code classification system by using memory-based learning and information retrieval technique",
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.",
author = "Lim, {Heui Seok} and Lee, {Won Kyu Hoon} and Kim, {Hyeon Chul} and Jeong, {Soon Young} and Yu, {Heon Chang}",
year = "2005",
doi = "10.1007/11562382_53",
language = "English",
isbn = "3540291865",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
pages = "577--582",
booktitle = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
note = "2nd Asia Information Retrieval Symposium, AIRS 2005 ; Conference date: 13-10-2005 Through 15-10-2005",
}