Augmenting personal IR Readings Review Two

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

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?

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

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.

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” p 1 - Page. Rank for individuals? - Page. Rank for the exact situation? - Smart crawling based on a profile?

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?

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

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

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”

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

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

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?

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)?