Please use this identifier to cite or link to this item: https://doi.org/10.1016/j.cad.2011.08.002
Title: Learning the "whys": Discovering design rationale using text mining - An algorithm perspective
Authors: Liang, Y.
Liu, Y. 
Kwong, C.K.
Lee, W.B.
Keywords: Design rationale
Patent mining
Rationale discovery
Rationale representation
Text Mining
Issue Date: Oct-2012
Source: Liang, Y., Liu, Y., Kwong, C.K., Lee, W.B. (2012-10). Learning the "whys": Discovering design rationale using text mining - An algorithm perspective. CAD Computer Aided Design 44 (10) : 916-930. ScholarBank@NUS Repository. https://doi.org/10.1016/j.cad.2011.08.002
Abstract: Collecting design rationale (DR) and making it available in a well-organized manner will better support product design, innovation and decision-making. Many DR systems have been developed to capture DR since the 1970s. However, the DR capture process is heavily human involved. In addition, with the increasing amount of DR available in archived design documents, it has become an acute problem to research a new computational approach that is able to capture DR from free textual contents effectively. In our previous study, we have proposed an ISAL (issue, solution and artifact layer) model for DR representation. In this paper, we focus on algorithm design to discover DR from design documents according to the ISAL modeling. For the issue layer of the ISAL model, we define a semantic sentence graph to model sentence relationships through language patterns. Based on this graph, we improve the manifold-ranking algorithm to extract issue-bearing sentences. To discover solution-reason bearing sentences for the solution layer, we propose building up two sentence graphs based on candidate solution-bearing sentences and reason-bearing sentences respectively, and propagating information between them. For artifact information extraction, we propose two term relations, i.e. positional term relation and mutual term relation. Using these relations, we extend our document profile model to score the candidate terms. The performance and scalability of the algorithms proposed are tested using patents as research data joined with an example of prior art search to illustrate its application prospects. © 2011 Elsevier Ltd. All rights reserved.
Source Title: CAD Computer Aided Design
URI: http://scholarbank.nus.edu.sg/handle/10635/68284
ISSN: 00104485
DOI: 10.1016/j.cad.2011.08.002
Appears in Collections:Staff Publications

Show full item record
Files in This Item:
There are no files associated with this item.

SCOPUSTM   
Citations

17
checked on Dec 7, 2017

WEB OF SCIENCETM
Citations

12
checked on Nov 23, 2017

Page view(s)

30
checked on Dec 11, 2017

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.