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Online Matching and Adwords Aranyak Mehta Google Research Mountain View, CA Search Adver=sing (Adwords) Queries Bidding (online) (offline) users adver=sers Search engine Queries Bidding (online) (offline) users adver=sers Search engine Find matching Score candidates Run auc3on candidates Queries Bidding (online) (offline) users adver=sers Search engine Find matching Score candidates Run auc3on candidates •  Adver=ser Budgets => Demand Constraint => Matching Display ads •  Demand is offline from adver=sers •  Targe=ng •  Quan=ty (“1M ads”) •  Supply is online from page views Ad Exchanges Publisher Ad Network Ad Exchange Publisher Ad Network Publisher Ad Network … Many other examples from adver=sing and outside. Theory to Prac=ce •  Details of the implementa=on: –  CTR, CPC, pay-‐per-‐click, Second price auc=on, Posi=on Normalizers. •  Objec=ve func=ons (in order): –  User’s u=lity –  Adver=ser ROI –  Short term Revenue / Long term growth Online Bipar=te Matching •  Match upon arrival, irrevocably •  Maximize size of the matching . . . . . . Known in Arrive advance Online The Core difficulty

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Search Adver)sing (Adwords) Short term Revenue / Long term growth Known iid. Bipar)te Matching. 1-‐1/e (op)mal). Vertex Weighted. Matching. Adwords

Online Matching and Adwords PDF

54 Pages·2011·3.28 MB·English

by Aranyak Mehta

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by Aranyak Mehta| 2011| 54 pages| 3.28| English

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Search Adver)sing (Adwords) Short term Revenue / Long term growth Known iid. Bipar)te Matching. 1-‐1/e (op)mal). Vertex Weighted. Matching. Adwords

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Author:	Aranyak Mehta
Publication Year:	2011
Pages:	54
Language:	English
File Size:	3.28
Format:	PDF
Price:	FREE

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