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Information Re-Retrieval: Repeat Queries in Yahoo’s Logs Jaime Teevan, Eytan Adar, Rosie Jones, Michael A. S. Potts SIGIR 2007.

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Presentation on theme: "Information Re-Retrieval: Repeat Queries in Yahoo’s Logs Jaime Teevan, Eytan Adar, Rosie Jones, Michael A. S. Potts SIGIR 2007."— Presentation transcript:

1 Information Re-Retrieval: Repeat Queries in Yahoo’s Logs Jaime Teevan, Eytan Adar, Rosie Jones, Michael A. S. Potts SIGIR 2007

2 Motivation Re-finding information is a common activity of Web search What is the intention of re-finding information? What factors favor/indicate user’s re- finding of information?

3 Dataset 114 Yahoo users search trace over 1 year (Aug 2004 – July 2005) –115 queries / trace –Considered as repeat when separated > 30 minutes 119 volunteers in a controlled experiment –users are asked to repeat one query made 30 mins to 1 hour ago

4 Techniques used Normalizing query terms –Capitalization, stop words removal, duplicate words removal, extra white space, stemming –Word order (e.g. “new york department of state” and “department of state new york”) –Non-alphanumerics (e.g. “sub-urban” vs “sub urban”) –Word merge (e.g. “wal mart” vs “walmart”) –Domain (e.g. hotmail vs hotmail.com) –Words swap (e.g. “american embassy london” vs “american consulate london”) SVM classifier –Applied to predict whether a result will be clicked again

5 Discovery Navigation query is one major type of re-finding information –Bank, news, mail –.com,.edu,.net Rank changes affects re- finding

6 Discovery Memory fades –Control experiment 30% are mis-remembered (36/119) 27 out of 36 are equivalent after normalization –Yahoo Logs  Indicators of repeat click –# clicks in first query –# clicks in previous query –# unique clicks in previous query


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