1. Augmenting (personal) IR
Readings Review
Two Topic Discussions
Evaluation Papers returned & discussed
Wildcard Week ideas
Papers and Projects checkin time

2. What do we mean by augment?
Douglas Englebart’s system
GUI
Interaction
Connectivity
Management
Improve upon
Extend user capabilities
Do what you want, but faster
“Do what I mean, not what I say”
What are some ways to augment?

3. What is Personalization?
In computing?
Optimized
System specific
In interfaces?
Modes of interaction
Appropriate for user level
For IR?
Results
Time
Mode
(Relevance) Feedback

4. Personalized IR system design
How would you design a personal IR system?
Who would use it?
How would you learn about them?
Interests
Sources
Preferences
How do you evaluate a personal system?
Understanding users is the key to personalizing search or search interfaces.

5. Letizia Interleaving browsing with (automated) search
Augmented browsing = less searching?
Understanding your usage preferences
“Behavior based”
Letizia explores for you
“doing concurrent, autonomous exploration of links from the user’s current position” p1
PageRank for individuals?
PageRank for the exact situation?
Smart crawling based on a profile?

6. Letizia’s Inferences
What you do tells the systems your interests and habits
List of keywords about your interests
Persistence of interest issues
Shifts
Time to restate interest
Automated queries, keyword matches
Doesn’t get in the way (much)
What about the interface?
Making Web search better?

7. Siteseer “Personalized navigation for the Web” Isn’t this a CF system?
Bookmarks are key indicators of interest
Category fits
Implicit recommendations

8. How to personalize the Web: WBI
Interests are bookmarks or home pages
Links
Text
Proxy-like between the user the Web
Agent like functions
Monitor - records features
Editor - tweaks retrieved information
Generator - request to response
Autonomous agent - triggers

9. Outride Data mining for personalized search
Fast model fitting for profiles
Search keyword augmentation
Interests
Preferences
“Contextual Computing”
Just in time information
Situational
More than content analysis
“Author relevancy”

10. Personalized Search Efficiency
Contextualization
Activity
Availability
Individualization
User goals (models of Iseek)
(Past) behavior
Interface
Awareness and customization

11. Personalization vs. Customization
What’s the difference?
For a system, for a user
Interaction methods, selection methods
My.yahoo.com vs. amazon.com
AskJeeves vs. a Reference Librarian

12. Topic Presentations What do these systems seem to offer?
How would you use them?
What’s different than you expected?
Better or Worse?
From your deign ideas?

13. WIRED System Evaluations
Install IR software
Set up documents for indexing
What types of documents
Sizes, formats, time to index?
Perform some searches
Note search functionality
Describe (screen shot?) interface for search
Examine results
Describe (screen shot?) results page/screen
Rotate, use subset of documents
Note differences in queries
What model, index, system do you think the system uses (based on class discussions & readings)?