Modeling of Tacit Knowledge and Its Application Case Study: Web Page Layout Design

Abstract

A method for modeling a tacit knowledge has been developed. Tacit knowledge is a type of knowledge that is difficult to describe with words or symbols such as sports techniques, design skills, etc. It is difficult for us to obtain and share this type of knowledge. In this paper, we discuss a new method to create a model of tacit knowledge by showing an example of web site designing. Usually, capable designers can express their intensions precisely through their works. This is to say, appearances of their works reflect their intention. Thus, it is expected that capable designers' tacit knowledge can be extracted from their works. Knowledge of the design was extracted from actual web pages on the Internet. Then, knowledge models were created by utilizing a Bayesian network. The created models were verified by LOOCV technique. The result shows that one of the created models illustrates part of a designers' knowledge accurately.

A comparison of Bayesian networks learning algorithms: A case study of webpage layout design

“…A scoring-based algorithm uses local search (LS) in the space of directed acyclic graphs (DAGs) [4]. These algorithms assign a score to each candidate Bayesian network and try to maximize it with some heuristic search algorithm [5].…”

“…There are numerous theories that deal with effect of color of webpage on users impression, whereas there are a few researches in which how layout items reflect web pages images. Thus, the authors have developed a model which represents design knowledge of website layout based on Bayesian network technique [4]. In order to build appropriate models, several algorithms for learning Bayesian networks have been developed.…”