An Online Causal Inference Framework for Modeling and Designing Systems Involving User Preferences: A State-Space Approach
Joint Authors
Delibalta, Ibrahim
Baruh, Lemi
Kozat, Suleyman Serdar
Source
Journal of Electrical and Computer Engineering
Issue
Vol. 2017, Issue 2017 (31 Dec. 2017), pp.1-11, 11 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2017-06-22
Country of Publication
Egypt
No. of Pages
11
Main Subjects
Information Technology and Computer Science
Abstract EN
We provide a causal inference framework to model the effects of machine learning algorithms on user preferences.
We then use this mathematical model to prove that the overall system can be tuned to alter those preferences in a desired manner.
A user can be an online shopper or a social media user, exposed to digital interventions produced by machine learning algorithms.
A user preference can be anything from inclination towards a product to a political party affiliation.
Our framework uses a state-space model to represent user preferences as latent system parameters which can only be observed indirectly via online user actions such as a purchase activity or social media status updates, shares, blogs, or tweets.
Based on these observations, machine learning algorithms produce digital interventions such as targeted advertisements or tweets.
We model the effects of these interventions through a causal feedback loop, which alters the corresponding preferences of the user.
We then introduce algorithms in order to estimate and later tune the user preferences to a particular desired form.
We demonstrate the effectiveness of our algorithms through experiments in different scenarios.
American Psychological Association (APA)
Delibalta, Ibrahim& Baruh, Lemi& Kozat, Suleyman Serdar. 2017. An Online Causal Inference Framework for Modeling and Designing Systems Involving User Preferences: A State-Space Approach. Journal of Electrical and Computer Engineering،Vol. 2017, no. 2017, pp.1-11.
https://search.emarefa.net/detail/BIM-1175215
Modern Language Association (MLA)
Delibalta, Ibrahim…[et al.]. An Online Causal Inference Framework for Modeling and Designing Systems Involving User Preferences: A State-Space Approach. Journal of Electrical and Computer Engineering No. 2017 (2017), pp.1-11.
https://search.emarefa.net/detail/BIM-1175215
American Medical Association (AMA)
Delibalta, Ibrahim& Baruh, Lemi& Kozat, Suleyman Serdar. An Online Causal Inference Framework for Modeling and Designing Systems Involving User Preferences: A State-Space Approach. Journal of Electrical and Computer Engineering. 2017. Vol. 2017, no. 2017, pp.1-11.
https://search.emarefa.net/detail/BIM-1175215
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1175215