1. Inferring People’s Site Preference in Web Search
Progress Report
Bin Tan

2. Problem Reiterated People prefer some sites to others in web search.
Preferences may change with topics.
How to remember a user’s site preference?

3. Examples DAIS: ranked 14th in Google
Hints from past queries: “dais” “dais uiuc”
Paper search → CiteSeer or ACM Portal?

4. Basic Approach Store a user’s search history in a log file
<Q, W>: Q - query W - clicked websites
Given a new query, find similar past queries and use the associated clicked website information to infer the user’s site preference

5. Basic Approach (cont.)
If a search result for the current query is from the most preferred site, move it to the top of the list
Nearest Neighbor paradigm

6. How to represent Q To capture the information need of a past search
Query keywords
Frequent terms in the results (or only the clicked ones?)
Other features like # results in pdf format

7. What to include in W Clicked result ≠ Relevant result ≠ Preferred site
Less time spent viewing a result → More likely the result is irrelevant
More clicks → Less confidence in site preference

8. Efficiency Issues 30 search a day → 10, 000 log entries a year
Inverted Index on query terms and sites

9. Another method? Random variable L: User likes a site for a query
Find w that maximize O(L=1|w,q) for a given q
P(q|w,L=1) ?