Study on the effects of semantic memory on icon complexity in cognitive domain

7Citations
Citations of this article
13Readers
Mendeley users who have this article in their library.

This article is free to access.

Abstract

It is a studying worthy problem whether highly visual complexity must bring low cognitive efficiency in icon design of visual interface. Although the visual noise of unreasonable and improper complexity seriously impacts the efficiency of users’ access and visual search tasks, few are able to determine the effects of memory on icon complexity in cognitive domain. The goal of the present study was to investigate the interaction between semantic memory and icon in a complexity perceptual layering method. The CP (Complexity of Presentation) and CM (Complexity of Memory) are presented in this article by a complex perceptual layering. Three laboratory experiments are conducted to assess the cognitive performances of three different complexities (low, medium and high) in three CP dimensions (shape feature, color feature, texture feature). Results revealed that, (1) One influence of semantic memory on icon complexity is the familiarity, the cognitive efficiency is enhanced when stimulus are processed in a high complex semantically meaningful way. (2) The cognitive performance of low complexity coding and high complexity coding is greater than the medium coding in the familiar test and the correlation test. (3) When searching for a similar target with stimulus in different complex levels, the gaze opacity and heat map data demonstrate the efficiency of medium-low and high-low are the highest. Based on the experimental results, it is validated that the interaction between semantic memory and icon complexity is a visual dimensionality reduction in a complexity perceptual layering.

Cite

CITATION STYLE

APA

Zhang, J., Xue, C., Shen, Z., Chen, X., Shao, J., Zhou, L., & Zhou, X. (2016). Study on the effects of semantic memory on icon complexity in cognitive domain. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9736, pp. 147–157). Springer Verlag. https://doi.org/10.1007/978-3-319-40030-3_16

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free