NDLI: A Markov chain model for integrating behavioral targeting into contextual advertising

Please wait, while we are loading the content...

Brand advertising, on-line audiences, and social media: invited talk

A Markov chain model for integrating behavioral targeting into contextual advertising

Probabilistic latent semantic user segmentation for behavioral targeted advertising

Argo: intelligent advertising by mining a user's interest from his photo collections

Scalable clustering and keyword suggestion for online advertisements

Inferring local synonyms for improving keyword suggestion in an on-line advertisement system

Data-driven text features for sponsored search click prediction

Revenue optimization with relevance constraint in sponsored search

Pricing guidance in ad sale negotiations: the PrintAds example

Online allocation of display advertisements subject to advanced sales contracts

Handling missing values in GPS surveys using survival analysis: a GPS case study of outdoor advertising

Ad quality on TV: predicting television audience retention

A Markov chain model for integrating behavioral targeting into contextual advertising

Content Provider	ACM Digital Library
Author	Bai, Fengshan Yan, Jun Chen, Zheng Wang, Gang Li, Ting Liu, Ning
Abstract	Both Contextual Advertising (CA) and Behavioral Targeting (BT) are playing important roles in online advertising market. Recently, the problem of how to integrate BT strategies into CA has attracted much attention from both industry and academia. However, to our best knowledge, few research works have been published to provide BT solutions in CA. In this paper, we propose a new notion of relevance between webpages and ads based on users' online click-through behaviors from BT's perspective. Compared with the classical behavior targeting method where only users' history interests are considered, we pay more attention to the click probability of ads from a webpage where the relevance between them is evaluated. Moreover, a combination model integrating behavioral relevance and contextual relevance for matching ads and webpags is presented. The model parameters are learnt from a dataset consisting of 200 webpages and 35,880 ads. Experimental results show that our integrated strategy indeed outperforms the strategies that only consider either behavioral relevance or contextual relevance. The best model achieves a 18.1% improvement in precision over single strategies.
Starting Page	1
Ending Page	9
Page Count	9
File Format	PDF
ISBN	9781605586717
DOI	10.1145/1592748.1592750
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2009-06-28
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Behavioral targeting Click-through data Contextual advertising Markov chain model
Content Type	Text
Resource Type	Article

Central Library (ISO-9001:2015 Certified)
Indian Institute of Technology Kharagpur
Kharagpur, West Bengal, India | PIN - 721302

See location in the Map
03222 282435
Mail: support@ndl.gov.in

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in