Authors:
Kazuko Takahashi
1
;
Hirofumi Taki
2
;
Shunsuke Tanabe
3
and
Wei Li
4
Affiliations:
1
Keiai University, Japan
;
2
Hosei University, Japan
;
3
Waseda University, Japan
;
4
Tokyo Institute of Technology, China
Keyword(s):
Automatic Coding System, Answers to Open-Ended Question, Occupation and Industry Coding, Natural Language Processing, Machine Learning, Confidence Level.
Related
Ontology
Subjects/Areas/Topics:
Applications
;
Applications and Case-studies
;
Artificial Intelligence
;
Knowledge Engineering and Ontology Development
;
Knowledge-Based Systems
;
Natural Language Processing
;
Pattern Recognition
;
Symbolic Systems
Abstract:
We develop a new automatic coding system with a three-grade confidence level corresponding to each of the national/international standard code sets for answers to open-ended questions regarding to respondent’s occupation and industry in social surveys including a national census. The “occupation and industry coding” is a necessary task for statistical processing. However, this task requires a great deal of labor and time-consuming. In addition, inconsistent results occur if the coders are not experts of coding. In formal research, various automatic coding systems have been developed, which are incomplete and generally unfriendly to a non-developer user. Our new system assigns three candidate codes to an answer for coders by SVMs (Support Vector Machines), and attaches a three-grade confidence level to the first-ranked predicted code by using classification scores to support a manual check of the results. The system is now open to the public through the Website of the Social Science Ja
pan Data Archive (SSJDA). After the submitted data file which followed the specified format is approved, the users can obtain files of codes for up to four kinds with a three-grade confidence level. In this paper, we describe our system and evaluate it.
(More)