William Eberle

According to our database, William Eberle authored at least 59 papers between 2006 and 2022.

Collaborative distances:

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

2022

Incorporating the Concepts of Fairness and Bias into an Undergraduate Computer Science Course to Promote Fair Automated Decision Systems.

Sheikh Rabiul Islam, Ingrid Russell, William Eberle, Darina Dicheva

Proceedings of the SIGCSE 2022: The 53rd ACM Technical Symposium on Computer Science Education, 2022

Self-Organizing Map-Based Graph Clustering and Visualization on Streaming Graphs.

Prabin B. Lamichhane, William Eberle

Proceedings of the IEEE International Conference on Data Mining Workshops, 2022

Discovering Breach Patterns on the Internet of Health Things: A Graph and Machine Learning Anomaly Analysis.

Prabin B. Lamichhane, Hannah Mannering, William Eberle

Proceedings of the Thirty-Fifth International Florida Artificial Intelligence Research Society Conference, 2022

2021

Explainable Artificial Intelligence Approaches: A Survey.

Sheikh Rabiul Islam, William Eberle, Sheikh Khaled Ghafoor, Mohiuddin Ahmed

CoRR, 2021

Visualization of Anomalies using Graph-Based Anomaly Detection.

Ramesh Paudel, Lauren Tharp, Dulce Kaiser, William Eberle, Gerald C. Gannod

Proceedings of the Thirty-Fourth International Florida Artificial Intelligence Research Society Conference, 2021

Anomaly Detection in Edge Streams Using Term Frequency-Inverse Graph Frequency (TF-IGF) Concept.

Prabin B. Lamichhane, William Eberle

Proceedings of the 2021 IEEE International Conference on Big Data (Big Data), 2021

Implications of Combining Domain Knowledge in Explainable Artificial Intelligence.

Sheikh Rabiul Islam, William Eberle

Proceedings of the AAAI 2021 Spring Symposium on Combining Machine Learning and Knowledge Engineering (AAAI-MAKE 2021), 2021

2020

An Approach For Concept Drift Detection in a Graph Stream Using Discriminative Subgraphs.

Ramesh Paudel, William Eberle

ACM Trans. Knowl. Discov. Data, 2020

Node Similarity For Anomaly Detection in Attributed Graphs.

Prajjwal Kandel, William Eberle

Proceedings of the Thirty-Third International Florida Artificial Intelligence Research Society Conference, 2020

Towards Quantification of Explainability in Explainable Artificial Intelligence Methods.

Sheikh Rabiul Islam, William Eberle, Sheikh K. Ghafoor

Proceedings of the Thirty-Third International Florida Artificial Intelligence Research Society Conference, 2020

Graph Filtering to Remove the "Middle Ground" for Anomaly Detection.

William Eberle, Lawrence Holder

Proceedings of the 2020 IEEE International Conference on Big Data (IEEE BigData 2020), 2020

Domain Knowledge Aided Explainable Artificial Intelligence for Intrusion Detection and Response.

Sheikh Rabiul Islam, William Eberle, Sheikh K. Ghafoor, Ambareen Siraj, Mike Rogers

Proceedings of the AAAI 2020 Spring Symposium on Combining Machine Learning and Knowledge Engineering in Practice, 2020

2019

Investigating bankruptcy prediction models in the presence of extreme class imbalance and multiple stages of economy.

Sheikh Rabiul Islam, William Eberle, Sheikh K. Ghafoor, Sid C. Bundy, Douglas A. Talbert, Ambareen Siraj

CoRR, 2019

Infusing domain knowledge in AI-based "black box" models for better explainability with application in bankruptcy prediction.

Sheikh Rabiul Islam, William Eberle, Sid C. Bundy, Sheikh Khaled Ghafoor

CoRR, 2019

Discovering Suspicious Patterns Using a Graph Based Approach.

Sirisha Velampalli, Lenin Mookiah, William Eberle

Proceedings of the Thirty-Second International Florida Artificial Intelligence Research Society Conference, 2019

Detecting the Onset of a Network Layer DoS Attack with a Graph-Based Approach.

Ramesh Paudel, Peter Harlan, William Eberle

Proceedings of the Thirty-Second International Florida Artificial Intelligence Research Society Conference, 2019

Gene Selection and Clustering of Breast Cancer Data.

Farzana Ahamed Bhuiyan, Md Bulbul Sharif, Paul Joshua Tinker, William Eberle, Douglas A. Talbert, Sheikh Khaled Ghafoor, Lewis J. Frey

Proceedings of the Thirty-Second International Florida Artificial Intelligence Research Society Conference, 2019

Detecting DoS Attack in Smart Home IoT Devices Using a Graph-Based Approach.

Ramesh Paudel, Timothy Muncy, William Eberle

Proceedings of the 2019 IEEE International Conference on Big Data (IEEE BigData), 2019

2018

A novel classifier ensemble approach for financial distress prediction.

Deron Liang, Chih-Fong Tsai, An-Jie Dai, William Eberle

Knowl. Inf. Syst., 2018

Personalized news recommendation using graph-based approach.

Lenin Mookiah, William Eberle, Maitrayi Mondal

Intell. Data Anal., 2018

Credit Default Mining Using Combined Machine Learning and Heuristic Approach.

Sheikh Rabiul Islam, William Eberle, Sheikh Khaled Ghafoor

CoRR, 2018

Prefix and Suffix Sequential Pattern Mining.

Rina Singh, Jeffrey A. Graves, Douglas A. Talbert, William Eberle

Proceedings of the Machine Learning and Data Mining in Pattern Recognition, 2018

Cognitive Health Prediction on the Elderly Using Sensor Data in Smart Homes.

Ramesh Paudel, Kimberlyn Dunn, William Eberle, Danielle Chaung

Proceedings of the Thirty-First International Florida Artificial Intelligence Research Society Conference, 2018

Mining Illegal Insider Trading of Stocks: A Proactive Approach.

Sheikh Rabiul Islam, Sheikh Khaled Ghafoor, William Eberle

Proceedings of the IEEE International Conference on Big Data (IEEE BigData 2018), 2018

2017

Detecting Vehicular Patterns Using a Graph-Based Approach.

Sirisha Velampalli, Lenin Mookiah, William Eberle

Proceedings of the 12th IEEE Conference on Visual Analytics Science and Technology, 2017

Mining Bad Credit Card Accounts from OLAP and OLTP.

Sheikh Rabiul Islam, William Eberle, Sheikh Khaled Ghafoor

Proceedings of the International Conference on Compute and Data Analysis, 2017

Novel Graph Based Anomaly Detection Using Background Knowledge.

Sirisha Velampalli, William Eberle

Proceedings of the Thirtieth International Florida Artificial Intelligence Research Society Conference, 2017

Anomalies in Students Enrollment Using Visualization.

Nishith Mukeshkumar Thakkar, Lenin Mookiah, Douglas A. Talbert, William Eberle

Proceedings of the Thirtieth International Florida Artificial Intelligence Research Society Conference, 2017

Detection of Anomalous Activity in Diabetic Patients Using Graph-Based Approach.

Ramesh Paudel, William Eberle, Douglas A. Talbert

Proceedings of the Thirtieth International Florida Artificial Intelligence Research Society Conference, 2017

Graph-Based Anomaly Detection on Smart Grid Data.

Lenin Mookiah, Chris Dean, William Eberle

Proceedings of the Thirtieth International Florida Artificial Intelligence Research Society Conference, 2017

2016

Data preprocessing issues for incomplete medical datasets.

Min-Wei Huang, Wei-Chao Lin, Chih-Wen Chen, Shih-Wen Ke, Chih-Fong Tsai, William Eberle

Expert Syst. J. Knowl. Eng., 2016

Report on the 29th International Florida Artificial Intelligence Research Society Conference (FLAIRS-29).

Zdravko Markov, Ingrid Russell, William Eberle

AI Mag., 2016

Never-Ending Medical Learning.

Douglas A. Talbert, William Eberle, Mei Liu

Proceedings of the AMIA 2016, 2016

2015

Instance selection by genetic-based biological algorithm.

Zong-Yao Chen, Chih-Fong Tsai, William Eberle, Wei-Chao Lin, Shih-Wen Ke

Soft Comput., 2015

Learning to detect representative data for large scale instance selection.

Wei-Chao Lin, Chih-Fong Tsai, Shih-Wen Ke, Chia-Wen Hung, William Eberle

J. Syst. Softw., 2015

Scalable anomaly detection in graphs.

William Eberle, Lawrence B. Holder

Intell. Data Anal., 2015

Survey of Crime Analysis and Prediction.

Lenin Mookiah, William Eberle, Ambareen Siraj

Proceedings of the Twenty-Eighth International Florida Artificial Intelligence Research Society Conference, 2015

Discovering Suspicious Behavior Using Graph-Based Approach.

Lenin Mookiah, William Eberle, Larry Holder

Proceedings of the Twenty-Eighth International Florida Artificial Intelligence Research Society Conference, 2015

Detecting Anomalies in Mobile Telecommunication Networks Using a Graph Based Approach.

Cameron Chaparro, William Eberle

Proceedings of the Twenty-Eighth International Florida Artificial Intelligence Research Society Conference, 2015

2014

Detecting suspicious behavior using a graph-based approach.

Lenin Mookiah, William Eberle, Lawrence B. Holder

Proceedings of the 9th IEEE Conference on Visual Analytics Science and Technology, 2014

Smart grid energy fraud detection using artificial neural networks.

Vitaly Ford, Ambareen Siraj, William Eberle

Proceedings of the 2014 IEEE Symposium on Computational Intelligence Applications in Smart Grid, 2014

A partitioning approach to scaling anomaly detection in graph streams.

William Eberle, Lawrence B. Holder

Proceedings of the 2014 IEEE International Conference on Big Data (IEEE BigData 2014), 2014

2013

Genetic algorithms in feature and instance selection.

Chih-Fong Tsai, William Eberle, Chi-Yuan Chu

Knowl. Based Syst., 2013

Incremental Anomaly Detection in Graphs.

William Eberle, Lawrence B. Holder

Proceedings of the 13th IEEE International Conference on Data Mining Workshops, 2013

Discovering Fraud in Online Classified Ads.

Alan Matthew McCormick, William Eberle

Proceedings of the Twenty-Sixth International Florida Artificial Intelligence Research Society Conference, 2013

Computer science widening the STEM education spectrum.

Christopher J. Morack, William Eberle

Proceedings of the IEEE Frontiers in Education Conference, 2013

Integrating communication skills in data structures and algorithms courses.

William Eberle, John Karro, Neal Lerner, Matthias F. Stallmann

Proceedings of the IEEE Frontiers in Education Conference, 2013

2012

Graph-Based Anomaly Detection Applied to Homeland Security Cargo Screening.

William Eberle, Lawrence B. Holder, Beverly Massengill

Proceedings of the Twenty-Fifth International Florida Artificial Intelligence Research Society Conference, 2012

2011

Graph-Based Knowledge Discovery: Compression versus Frequency.

William Eberle, Lawrence B. Holder

Proceedings of the Twenty-Fourth International Florida Artificial Intelligence Research Society Conference, 2011

2010

Using a Graph-Based Approach for Discovering Cybercrime.

William Eberle, Lawrence B. Holder, Jeffrey Graves

Proceedings of the Twenty-Third International Florida Artificial Intelligence Research Society Conference, 2010

2009

Applying graph-based anomaly detection approaches to the discovery of insider threats.

William Eberle, Lawrence B. Holder

Proceedings of the IEEE International Conference on Intelligence and Security Informatics, 2009

Discovering Anomalies to Multiple Normative Patterns in Structural and Numeric Data.

William Eberle, Lawrence B. Holder

Proceedings of the Twenty-Second International Florida Artificial Intelligence Research Society Conference, 2009

Special Track on Data Mining.

William Eberle, David Bisant

Proceedings of the Twenty-Second International Florida Artificial Intelligence Research Society Conference, 2009

Graph-based approaches to insider threat detection.

William Eberle, Lawrence B. Holder

Proceedings of the Fifth Cyber Security and Information Intelligence Research Workshop, 2009

Mining for insider threats in business transactions and processes.

William Eberle, Lawrence B. Holder

Proceedings of the IEEE Symposium on Computational Intelligence and Data Mining, 2009

2007

Anomaly detection in data represented as graphs.

William Eberle, Lawrence B. Holder

Intell. Data Anal., 2007

Discovering Structural Anomalies in Graph-Based Data.

William Eberle, Lawrence B. Holder

Proceedings of the Workshops Proceedings of the 7th IEEE International Conference on Data Mining (ICDM 2007), 2007

Mining for Structural Anomalies in Graph-based Data.

William Eberle, Lawrence B. Holder

Proceedings of the 2007 International Conference on Data Mining, 2007

2006

Detecting Anomalies in Cargo Using Graph Properties.

William Eberle, Lawrence B. Holder

Proceedings of the Intelligence and Security Informatics, 2006