Personalized recommendation on discount coupons

Teemu Mutanen, Sami Nousiainen, H. Liang

Research output: Contribution to conferenceConference articleScientific

Abstract

We present several recommendation approaches how discount coupon service could be personalized in order to cut down customer’s usage time. The Velo system is already implemented coupon service system in China with millions of users. The proposed approach makes use of customer and dispenser meta data together with previous user coupon prints in order to predict upcoming prints for a customer
Original languageEnglish
Number of pages6
Publication statusPublished - 2010
MoE publication typeNot Eligible
EventAnnual International Conference on Computer Science Education: Innovation and Technology - Special Track: Knowledge Discovery, KD 2010 - Phuket, Thailand
Duration: 6 Dec 20107 Dec 2010

Conference

ConferenceAnnual International Conference on Computer Science Education: Innovation and Technology - Special Track: Knowledge Discovery, KD 2010
Abbreviated titleKD 2010
CountryThailand
CityPhuket
Period6/12/107/12/10

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Keywords

  • Personalization
  • Discount Coupon
  • Recommendation Systems
  • User Modeling

Cite this

Mutanen, T., Nousiainen, S., & Liang, H. (2010). Personalized recommendation on discount coupons. Paper presented at Annual International Conference on Computer Science Education: Innovation and Technology - Special Track: Knowledge Discovery, KD 2010, Phuket, Thailand.
Mutanen, Teemu ; Nousiainen, Sami ; Liang, H. / Personalized recommendation on discount coupons. Paper presented at Annual International Conference on Computer Science Education: Innovation and Technology - Special Track: Knowledge Discovery, KD 2010, Phuket, Thailand.6 p.
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title = "Personalized recommendation on discount coupons",
abstract = "We present several recommendation approaches how discount coupon service could be personalized in order to cut down customer’s usage time. The Velo system is already implemented coupon service system in China with millions of users. The proposed approach makes use of customer and dispenser meta data together with previous user coupon prints in order to predict upcoming prints for a customer",
keywords = "Personalization, Discount Coupon, Recommendation Systems, User Modeling",
author = "Teemu Mutanen and Sami Nousiainen and H. Liang",
note = "Project code: 35520 ; Annual International Conference on Computer Science Education: Innovation and Technology - Special Track: Knowledge Discovery, KD 2010, KD 2010 ; Conference date: 06-12-2010 Through 07-12-2010",
year = "2010",
language = "English",

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Mutanen, T, Nousiainen, S & Liang, H 2010, 'Personalized recommendation on discount coupons' Paper presented at Annual International Conference on Computer Science Education: Innovation and Technology - Special Track: Knowledge Discovery, KD 2010, Phuket, Thailand, 6/12/10 - 7/12/10, .

Personalized recommendation on discount coupons. / Mutanen, Teemu; Nousiainen, Sami; Liang, H.

2010. Paper presented at Annual International Conference on Computer Science Education: Innovation and Technology - Special Track: Knowledge Discovery, KD 2010, Phuket, Thailand.

Research output: Contribution to conferenceConference articleScientific

TY - CONF

T1 - Personalized recommendation on discount coupons

AU - Mutanen, Teemu

AU - Nousiainen, Sami

AU - Liang, H.

N1 - Project code: 35520

PY - 2010

Y1 - 2010

N2 - We present several recommendation approaches how discount coupon service could be personalized in order to cut down customer’s usage time. The Velo system is already implemented coupon service system in China with millions of users. The proposed approach makes use of customer and dispenser meta data together with previous user coupon prints in order to predict upcoming prints for a customer

AB - We present several recommendation approaches how discount coupon service could be personalized in order to cut down customer’s usage time. The Velo system is already implemented coupon service system in China with millions of users. The proposed approach makes use of customer and dispenser meta data together with previous user coupon prints in order to predict upcoming prints for a customer

KW - Personalization

KW - Discount Coupon

KW - Recommendation Systems

KW - User Modeling

M3 - Conference article

ER -

Mutanen T, Nousiainen S, Liang H. Personalized recommendation on discount coupons. 2010. Paper presented at Annual International Conference on Computer Science Education: Innovation and Technology - Special Track: Knowledge Discovery, KD 2010, Phuket, Thailand.