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How can the preference information of a design team be computationally
extracted from their discussions? The method proposed in Chapter 4 links the
relations between what designers say in discussion and what they prefer in design with
an utterance-preference model and a preference transition model, and presents a
probabilistic approach to extracting preferential probabilities from transcripts of
design team discussion based on a time interval-based profile. It works to extract
preference information in an implicit way and as if the group is a single entity. The
probabilistic approach (PPT) for extracting the group’s preferential probabilities from
the transcript may be a potentially effective way to link the qualitative design
information that is generated by design teams with more quantitative design decision
making methods through the use of preference information.
How do the design preferences of a team evolve over time as the team changes its
priorities on the alternatives? This research shows how the design selection process
evolves over the design process. In the design selection process, when designers make
trade-offs, the design team’s preference may oscillate as well during the process.
From perspective of information entropy, a conjecture is that a design team starts with
lower certainty (higher entropy) and was more certain on the most-preferred choice
when the team reached the agreement. The results of this research on the two case
studies are consistent with this conjecture. One comment is that when additional
information is given to the team, this might not be true because the team may re-assess
all alternatives. The work in this research on time-based extraction of preferential
Object Description
| Title | Extraction of preferential probabilities from early stage engineering design team discussion |
| Author | Ji, Haifeng |
| Author email | haifengj@usc.edu; haifeng.ji@gmail.com |
| Degree | Doctor of Philosophy |
| Document type | Dissertation |
| Degree program | Industrial & Systems Engineering |
| School | Viterbi School of Engineering |
| Date defended/completed | 2008-08-19 |
| Date submitted | 2008 |
| Restricted until | Unrestricted |
| Date published | 2008-10-07 |
| Advisor (committee chair) | Yang, Maria C. |
| Advisor (committee member) |
Lu, Stephen Jin, Yan |
| Abstract | Activities in the early stage of engineering design typically include the generation of design choices and selection among these design choices. A key notion in design alternative selection is that of preference in which a designer or design team assigns priorities to a set of design choices. However, preferences become more challenging to assign on both a practical and theoretical level when done by a group of individuals. Preferences may also be explicitly obtained via surveys or questionnaires in which designers are asked to rank the choices, rate choice with values, or select a "most-preferred" choice. However, these methods are typically employed at a single point of time; therefore, it may not be practical to use surveys to elicit a team’s preference change and evolution throughout the process.; This research explores the text analysis on the design discussion transcripts and presents a probabilistic approach for implicitly extracting a projection of aggregated preference-related information from the transcripts. The approach in this research graphically represents how likely a choice is to be "most preferred" by a design team over time. For evaluation purpose, two approaches are established for approximating a team's "most preferred" choice in a probabilistic way from surveys of individual team members. A design selection experiment was conducted to determine possible correlations between the preferential probabilities estimated from the team's discussion and survey ratings explicitly stated by team members. Results suggest that there are strong correlations between extracted preferential probabilities and team intents that are stated explicitly, and that the proposed methods can provide a quantitative way to understand and represent qualitative design information using a low overhead information extraction method. |
| Keyword | preferences; probabilities; concept selection; design process; design decision-making |
| Language | English |
| Part of collection | University of Southern California dissertations and theses |
| Publisher (of the original version) | University of Southern California |
| Place of publication (of the original version) | Los Angeles, California |
| Publisher (of the digital version) | University of Southern California. Libraries |
| Provenance | Electronically uploaded by the author |
| Type | texts |
| Legacy record ID | usctheses-m1635 |
| Contributing entity | University of Southern California |
| Rights | Ji, Haifeng |
| Repository name | Libraries, University of Southern California |
| Repository address | Los Angeles, California |
| Repository email | cisadmin@lib.usc.edu |
| Filename | etd-Ji-2413 |
| Archival file | uscthesesreloadpub_Volume14/etd-Ji-2413.pdf |
Description
| Title | Page 146 |
| Contributing entity | University of Southern California |
| Repository email | cisadmin@lib.usc.edu |
| Full text | 134 How can the preference information of a design team be computationally extracted from their discussions? The method proposed in Chapter 4 links the relations between what designers say in discussion and what they prefer in design with an utterance-preference model and a preference transition model, and presents a probabilistic approach to extracting preferential probabilities from transcripts of design team discussion based on a time interval-based profile. It works to extract preference information in an implicit way and as if the group is a single entity. The probabilistic approach (PPT) for extracting the group’s preferential probabilities from the transcript may be a potentially effective way to link the qualitative design information that is generated by design teams with more quantitative design decision making methods through the use of preference information. How do the design preferences of a team evolve over time as the team changes its priorities on the alternatives? This research shows how the design selection process evolves over the design process. In the design selection process, when designers make trade-offs, the design team’s preference may oscillate as well during the process. From perspective of information entropy, a conjecture is that a design team starts with lower certainty (higher entropy) and was more certain on the most-preferred choice when the team reached the agreement. The results of this research on the two case studies are consistent with this conjecture. One comment is that when additional information is given to the team, this might not be true because the team may re-assess all alternatives. The work in this research on time-based extraction of preferential |
