Jingjing Zhang

Orcid: 0000-0002-6805-8685

Affiliations:
  • Indiana University, Bloomington, IN, USA


According to our database1, Jingjing Zhang authored at least 24 papers between 2007 and 2023.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

Online presence:

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Bibliography

2023
<i>When Algorithms Err</i> : Differential Impact of Early vs. Late Errors on Users' Reliance on Algorithms.
ACM Trans. Comput. Hum. Interact., February, 2023

Editorial: Some Thoughts on Reviewing for <i>Information Systems Research</i> and Other Leading Information Systems Journals.
Inf. Syst. Res., 2023

2022
Effects of Personalized Recommendations Versus Aggregate Ratings on Post-Consumption Preference Responses.
MIS Q., 2022

Recommender Systems, Ground Truth, and Preference Pollution.
AI Mag., 2022

2021
Effects of Personalized and Aggregate Top-N Recommendation Lists on User Preference Ratings.
ACM Trans. Inf. Syst., 2021

Understanding Longitudinal Dynamics of Recommender Systems with Agent-Based Modeling and Simulation.
CoRR, 2021

2020
Consumption and Performance: Understanding Longitudinal Dynamics of Recommender Systems via an Agent-Based Simulation Framework.
Inf. Syst. Res., 2020

Understanding the Impact of Individual Users' Rating Characteristics on the Predictive Accuracy of Recommender Systems.
INFORMS J. Comput., 2020

2019
Reeducing Recommender System Biases: An Investigation of Rating Display Designs.
MIS Q., 2019

2018
Effects of Online Recommendations on Consumers' Willingness to Pay.
Inf. Syst. Res., 2018

Exploring Explanation Effects on Consumers' Trust in Online Recommender Agents.
Int. J. Hum. Comput. Interact., 2018

2016
Classification, Ranking, and Top-K Stability of Recommendation Algorithms.
INFORMS J. Comput., 2016

Understanding Effects of Personalized vs. Aggregate Ratings on User Preferences.
Proceedings of the Joint Workshop on Interfaces and Human Decision Making for Recommender Systems co-located with ACM Conference on Recommender Systems (RecSys 2016), 2016

2015
Improving Stability of Recommender Systems: A Meta-Algorithmic Approach.
IEEE Trans. Knowl. Data Eng., 2015

2013
Do Recommender Systems Manipulate Consumer Preferences? A Study of Anchoring Effects.
Inf. Syst. Res., 2013

2012
Stability of Recommendation Algorithms.
ACM Trans. Inf. Syst., 2012

Impact of data characteristics on recommender systems performance.
ACM Trans. Manag. Inf. Syst., 2012

Iterative Smoothing Technique for Improving the Stability of Recommender Systems.
Proceedings of the Workshop on Recommendation Utility Evaluation: Beyond RMSE, 2012

2011
Anchoring effects of recommender systems.
Proceedings of the 2011 ACM Conference on Recommender Systems, 2011

2008
Analyzing Tree-Like Structures in Biomedical Images Based on Texture and Branching: An Application to Breast Imaging.
Proceedings of the Digital Mammography, 2008

A texture-based methodology for identifying tissue type in magnetic resonance images.
Proceedings of the 2008 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, 2008

A web-accessible framework for the automated storage and texture analysis of biomedical images.
Proceedings of the 2008 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, 2008

2007
Analysis of texture patterns in medical images with an application to breast imaging.
Proceedings of the Medical Imaging 2007: Computer-Aided Diagnosis, 2007

An Effective and Efficient Technique for Searching for Similar Brain Activation Patterns.
Proceedings of the 2007 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, 2007


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