NDLI: Hidden Conditional Random Fields with Deep User Embeddings for Ad Targeting

Content Provider	IEEE Xplore Digital Library
Author	Djuric, Nemanja Radosavljevic, Vladan Grbovic, Mihajlo Bhamidipati, Narayan
Copyright Year	2014
Abstract	Estimating a user's propensity to click on a display ad or purchase a particular item is a critical task in targeted advertising, a burgeoning online industry worth billions of dollars. Better and more accurate estimation methods result in improved online user experience, as only relevant and interesting ads are shown, and may also lead to large benefits for advertisers, as targeted users are more likely to click or make a purchase. In this paper we address this important problem, and propose an approach for improved estimation of ad click or conversion probability based on a sequence of user's online actions, modeled using Hidden Conditional Random Fields (HCRF) model. In addition, in order to address the sparsity issue at the input side of the HCRF model, we propose to learn distributed, low-dimensional representations of user actions through a directed skip-gram, a neural architecture suitable for sequential data. Experimental results on a real-world data set comprising thousands of user sessions collected at Yahoo servers clearly indicate the benefits and the potential of the proposed approach, which outperformed competing state-of-the-art algorithms and obtained significant improvements in terms of retrieval measures.
Starting Page	779
Ending Page	784
File Size	342092
Page Count	6
File Format	PDF
ISSN	15504786
e-ISBN	9781479943029
DOI	10.1109/ICDM.2014.150
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-12-14
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Hidden Markov models Predictive models Advertising Browsers Context modeling Context Support vector machines hidden CRF ad targeting click modeling purchase prediction
Content Type	Text
Resource Type	Article

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
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9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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