1. Modeling Information Navigation : Implication for Information Architecture Craig S. Miller 이주우

2. INTRODUCTION MODELING INFORMATION NAVIGATION SIMULATIONS COLLECTING DETAILED HUMAN PERFORMANCE RESULTS DETAILED SIMULATIONS AND COMPARISONS GENERAL DISCUSSION APPENDIX CONTENTS

3. 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)

4. 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

5. 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

6. 2.3. Modeling Navigation Strategies 2.4. Detailed Example 2.3. Modeling Navigation Strategies

7. 2.4. Detailed Example 19 link evaluation 8 link selection 5 back action

8. 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

9. 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

10. 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

11. 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

12. 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

13. 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

14. 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

15. Simulation 1Simulation 2Simulation 3 Parameter Reliability : 0, 0.5, 1 Threshold : 0.75, 0.25 Adding variation to the judges’s average rating Incrementally increased the variance Spearman rank Correlation 0.7390.8510.790~0.832 Pearson Correlation 0.6920.7900.851~0.869 Simulation

16. 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