TY - JOUR
T1 - Labeling design documents based on operators' consensus-A case study of robotic design
AU - Jie, Sun
AU - Feng, Lu Wen
AU - Tong, Loh Han
N1 - Funding Information:
The authors would like to thank the support from Singapore Ministry of Education's AcRF Tier 1 funding (R-265-000-209-112/113). The authors also appreciate the suggestions and support from Zhang Jiaming and Wong Chern Yuen from National University of Singapore.
PY - 2010/1
Y1 - 2010/1
N2 - Designers usually begin with a database to look for historical design solution, available experience and techniques through design documents, when initiating a new design. This database is a collection of labeled design documents under a few of predefined categories. However, little work has been done on labeling a relatively small number of design documents for information organization, so that most of design documents in this database can be automatically categorized. This paper initiates a study on this topic and proposes a methodology in four steps: design document collection, documents labeling, finalization of documents labeling and categorization of design database. Our discussion in this paper focuses on the first three steps. The key of this method is to collect relatively small number of design documents for manual labeling operation, and unify the effective labeling results as the final labels in terms of labeling agreement analysis and text classification experiment. Then these labeled documents are utilized as training samples to construct classifiers, which can automatically give appropriate labels to each design document. With this method, design documents are labeled in terms of the consensus of operators' understanding, and design information can be organized in a comprehensive and universally accessible way. A case study of labeling robotic design documents is used to demonstrate the proposed methodology. Experimental results show that this method can significantly benefit efficient design information search.
AB - Designers usually begin with a database to look for historical design solution, available experience and techniques through design documents, when initiating a new design. This database is a collection of labeled design documents under a few of predefined categories. However, little work has been done on labeling a relatively small number of design documents for information organization, so that most of design documents in this database can be automatically categorized. This paper initiates a study on this topic and proposes a methodology in four steps: design document collection, documents labeling, finalization of documents labeling and categorization of design database. Our discussion in this paper focuses on the first three steps. The key of this method is to collect relatively small number of design documents for manual labeling operation, and unify the effective labeling results as the final labels in terms of labeling agreement analysis and text classification experiment. Then these labeled documents are utilized as training samples to construct classifiers, which can automatically give appropriate labels to each design document. With this method, design documents are labeled in terms of the consensus of operators' understanding, and design information can be organized in a comprehensive and universally accessible way. A case study of labeling robotic design documents is used to demonstrate the proposed methodology. Experimental results show that this method can significantly benefit efficient design information search.
KW - Hypothesis test
KW - Knowledge retrieval
KW - Product design
KW - Text classification
UR - http://www.scopus.com/inward/record.url?scp=70350571096&partnerID=8YFLogxK
U2 - 10.1016/j.compind.2009.07.002
DO - 10.1016/j.compind.2009.07.002
M3 - Article
AN - SCOPUS:70350571096
SN - 0166-3615
VL - 61
SP - 66
EP - 74
JO - Computers in Industry
JF - Computers in Industry
IS - 1
ER -