Matches in ScholarlyData for { <https://w3id.org/scholarlydata/inproceedings/www2009/paper/107> ?p ?o. }
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- 107 type InProceedings.
- 107 label "Predicting Click Through Rate for Job Listings".
- 107 sameAs 107.
- 107 abstract "Click Through Rate (CTR) is an important metric for ad systems, job portals, recommendation systems. CTR impacts publisher's revenue, advertiser's bid amounts in "pay for performance" business models. We learn regression models using features of the job, optional click history of job, features of "related" jobs. We show that our models predict CTR much better than predicting avg. CTR for all job listings, even in absence of the click history for the job listing.".
- 107 hasAuthorList authorList.
- 107 isPartOf proceedings.
- 107 keyword "Poster Session".
- 107 title "Predicting Click Through Rate for Job Listings".