Research Papers

A New Design Rationale Representation Model for Rationale Mining

[+] Author and Article Information
Ying Liu1

Mechanical Engineering, National University of Singapore, Singapore 117576mpeliuy@nus.edu.sg

Yan Liang, Chun Kit Kwong, Wing Bun Lee

Industrial and Systems Engineering, Hong Kong Polytechnic University, Hong Kong SAR, China


Corresponding author.

J. Comput. Inf. Sci. Eng 10(3), 031009 (Sep 03, 2010) (10 pages) doi:10.1115/1.3470018 History: Received June 30, 2009; Revised July 28, 2010; Published September 03, 2010

The management of design rationale (DR) in engineering design is an important task since DR is often regarded as crucial information in design decision support and design analysis. The existing DR systems largely rely on human efforts in capturing DRs along design activities according to some predefined DR models. However, these systems require heavy human involvement and they do not have the capacity to extract DRs from design archival documents, which contain rich DR information but are usually unstructured or semistructured texts, e.g., design documents, service reports, and test reports. In view of such challenges, it has motivated us to propose a new DR model to intelligently discover DRs from design archival documents. In this paper, we propose an issue, solution and artifact layer (ISAL) model for DR representation and approaches for rationale information discovery from design archival documents. We also introduce a DR repository construction platform based on the ISAL model by integrating rationale information from both design archival documents and design processes. Using patent documents as our research data, we conduct a conceptual comparison and experimental study of DR discovery especially for artifact information extraction. Results demonstrate the merits of our proposal. Lastly, we discuss potential applications by taking advantage of our ISAL model.

Copyright © 2010 by American Society of Mechanical Engineers
Topics: Design , Patents
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Figure 1

DR representation in a single document

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Figure 2

An example of solution and its corresponding effect

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Figure 3

The framework of artifact information extraction

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Figure 4

The framework of DR repository construction

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Figure 5

An example of DR representation using ISAL

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Figure 6

An example of DR representation using IBIS

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Figure 7

Precision of DP model and our approach

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Figure 8

Examples of phrases extracted by DP and our approach

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Figure 9

An example of artifact information extracted

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Figure 10

An example of DR network



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