modeling information navigation : implication for information architecture craig s. miller 이주우
TRANSCRIPT
Modeling Information Navigation :
Implication for Information Architecture
Craig S. Miller
이주우
INTRODUCTION
MODELING INFORMATION NAVIGATION
SIMULATIONS
COLLECTING DETAILED HUMAN PERFORMANCE RESULTS
DETAILED SIMULATIONS AND COMPARISONS
GENERAL DISCUSSION
APPENDIX
CONTENTS
INTRODUCTION
The identification of factors that affect the usability of the World Wide Web has become increasingly important
How a site’s information architecture impacts a user’s ability
Our goals is
- To show the viability of a computational model
- Advice to Web site designers
-Use these costs identifying effective information architectures
MESA (Method for Evaluating Site Architectures)
MODELING INFORMATION NAVIGATION
Our goal is to simulate common pattern of user interaction with Web site
Guide abstraction and model construction
-The limited capacity principle
-The simplicity principle
-The rationality principle
2.1. Representing a Web Site
2.2. Modeling the Browser and User Actions
Selecting a link (and attending to and identifying a new page)
Pressing the Back button (and attending to and identifying a new page)
Checking a link and evaluating its relevance
2.3. Modeling Navigation Strategies
MESA navigates a Web site by serially executing
- The threshold strategy
- The comparison strategy
- The opportunistically strategy
2.3. Modeling Navigation Strategies
2.4. Detailed Example
2.3. Modeling Navigation Strategies
2.4. Detailed Example
19 link evaluation
8 link selection
5 back action
2.4. Detailed Example
Cognitive limitations contribute to additional navigation cost
-first : only one link can be evaluated at a time
-second : page C needs to be scanned a second time
-third : memory limitation
2.6. Simulation Parameters
Time Constants
Our model estimate navigation times for finding an item
(link evaluation, link selection, and pressing the Back button)
Result from hierarchical menu selection studies. D.P.Miller(1981) reported that humans searching through an 8x8 menu system
Link evaluation / link selection
250 / 500 : 2.9sec
250 / 250 : 2.4sec
250 / 750 : 3.4sec
2.6. Simulation Parameters
Setting Relevance Values for Link Labels
The comparison to menu selection results assumes ideal link. BUT…
- g is produced from a standard normal distribution
- n is noise factor
3. SIMULATIONS
3.1. Modeling Structure and Link Ambiguity
First, explore the effect of label ambiguity on the structure
- Ambiguity link needs more time
- 8x8x8 architecture is faster→ slower
- noise level 0.4
3.2. impact of Time Costs
Although changing the time costs will affect absolute simulation time
-regardless of the time cost
3.3. Impact of Bottom-Level Noise
4. COLLECTING DETAILED HUMAN PERFORMANCE RESULTS
4.1. Method
- Participants : 45, at least 10hr, at least 18year, frequently used the Web
- Materials : 6 high level, 37 low level categories
4.2. Results
Simulation
45 participants Three Structure
Looking for a total of eight items
360 task(15X8X3)
Parameter
500msec : link selecting and pressing the back button
250msec : evaluating each link
Simulation 1 Simulation 2 Simulation 3
ParameterReliability : 0, 0.5, 1Threshold : 0.75 , 0.25
Adding variation to the judges’s average rating
Incrementally increased the
variance
Spearman rank
Correlation0.739 0.851 0.790~0.832
Pearson Correlation
0.692 0.790 0.851~0.869
Simulation
Optimal number of 8 selections per display
12~32 links per page (Larson and Czerwinski(1998))
Two-tired structures produce faster results than Three-tiered in followed three conditions
Three-tired structure may be optimal when the level of label quality is the same across all levels.
Discussion