Joseph Bockhorst

According to our database, Joseph Bockhorst authored at least 18 papers between 2000 and 2021.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2021

Graph Neural Networks to Predict Customer Satisfaction Following Interactions with a Corporate Call Center.

Teja Kanchinadam, Zihang Meng, Joseph Bockhorst, Vikas Singh, Glenn Fung

CoRR, 2021

2020

Designing and deploying insurance recommender systems using machine learning.

Maleeha Qazi, Kaya Tollas, Teja Kanchinadam, Joseph Bockhorst, Glenn Fung

WIREs Data Mining Knowl. Discov., 2020

2019

Probabilistic-Logic Bots for Efficient Evaluation of Business Rules Using Conversational Interfaces.

Joseph Bockhorst, Devin Conathan, Glenn Moo Fung

Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018

Using Discriminative Graphical Models for Insurance Recommender Systems.

Teja Kanchinadam, Maleeha Qazi, Joseph Bockhorst, Mary Y. Morell, Katie J. Meissner, Glenn Fung

Proceedings of the 17th IEEE International Conference on Machine Learning and Applications, 2018

2017

Predicting Self-reported Customer Satisfaction of Interactions with a Corporate Call Center.

Joseph Bockhorst, Shi Yu, Luisa F. Polanía, Glenn Fung

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2017

2016

Using Temporal Discovery and Data-Driven Journey-Maps to Predict Customer Satisfaction.

Joe Bockhorst, Yingjian Wang, Sukrat Gupta, Maleeha Qazi, Mingju Sun, Glenn Fung

Proceedings of the 15th IEEE International Conference on Machine Learning and Applications, 2016

2011

A Machine Learning Approach to Identifying Sections in Legal Briefs.

Scott Vanderbeck, Joseph Bockhorst, Chad Oldfather

Proceedings of The 22nd Midwest Artificial Intelligence and Cognitive Science Conference 2011, 2011

2010

Auto-Regressive HMM Inference with Incomplete Data for Short-Horizon Wind Forecasting.

Chris Barber, Joseph Bockhorst, Paul Roebber

Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, 2010

2007

Discovering Patterns in Biological Sequences by Optimal Segmentation.

Joseph Bockhorst, Nebojsa Jojic

Proceedings of the UAI 2007, 2007

Connecting quantitative regulatory-network models to the genome.

Yue Pan, Tim Durfee, Joseph Bockhorst, Mark Craven

Proceedings of the Proceedings 15th International Conference on Intelligent Systems for Molecular Biology (ISMB) & 6th European Conference on Computational Biology (ECCB), 2007

2004

Markov Networks for Detecting Overalpping Elements in Sequence Data.

Joseph Bockhorst, Mark Craven

Proceedings of the Advances in Neural Information Processing Systems 17 [Neural Information Processing Systems, 2004

FOIL-D: Efficiently Scaling FOIL for Multi-relational Data Mining of Large Datasets.

Joseph Bockhorst, Irene M. Ong

Proceedings of the Inductive Logic Programming, 14th International Conference, 2004

2003

A Bayesian Network Approach to Operon Prediction.

Joseph Bockhorst, Mark W. Craven, David Page, Jude W. Shavlik, Jeremy D. Glasner

Bioinform., 2003

Predicting bacterial transcription units using sequence and expression data.

Joseph Bockhorst, Yu Qiu, Jeremy D. Glasner, Mingzhu Liu, Frederick R. Blattner, Mark Craven

Proceedings of the Eleventh International Conference on Intelligent Systems for Molecular Biology, June 29, 2003

2002

Exploiting Relations Among Concepts to Acquire Weakly Labeled Training Data.

Joseph Bockhorst, Mark Craven

Proceedings of the Machine Learning, 2002

2001

Refining the Structure of a Stochastic Context-Free Grammar.

Joseph Bockhorst, Mark Craven

Proceedings of the Seventeenth International Joint Conference on Artificial Intelligence, 2001

2000

A Probabilistic Learning Approach to Whole-Genome Operon Prediction.

Mark W. Craven, David Page, Jude W. Shavlik, Joseph Bockhorst, Jeremy D. Glasner

Proceedings of the Eighth International Conference on Intelligent Systems for Molecular Biology, 2000

Using Multiple Levels of Learning and Diverse Evidence to Uncover Coordinately Controlled Genes.

Mark W. Craven, David Page, Jude W. Shavlik, Joseph Bockhorst, Jeremy D. Glasner

Proceedings of the Seventeenth International Conference on Machine Learning (ICML 2000), Stanford University, Stanford, CA, USA, June 29, 2000