Tom Johnsten

Publication Activity (10 Years)

Years Active: 1999-2022
Publications (10 Years): 10

Top Topics

Top Venues

Publications

Tom Johnsten, Aishwarya Prakash, Grant T. Daly, Ryan G. Benton, Tristan Clark
Computational framework for generating synthetic signal peptides. BCB (2022)
Blake A. Johns, Ryan G. Benton, Tom Johnsten, David M. Bourrie
RARE: Rare Action Rule Exploration. IEEE BigData (2021)
Yihe Zhang, Xu Yuan, Sytske K. Kimball, Eric Rappin, Li Chen, Paul J. Darby III, Tom Johnsten, Lu Peng, Boisy Pitre, David Bourrie, Nian-Feng Tzeng
Precise Weather Parameter Predictions for Target Regions via Neural Networks. ECML/PKDD (5) (2021)
Wyatt Green, Tom Johnsten, Ryan G. Benton
TADS: Transformation of Anomalies in Data Streams. IEEE BigData (2020)
Suresh K. Choubey, Ryan Benton, Tom Johnsten
Dynamic Thresholding Leading to Optimal Inventory Maintenance. IEEE BigData (2020)
Yihe Zhang, Jiadong Lou, Li Chen, Xu Yuan, Jin Li, Tom Johnsten, Nian-Feng Tzeng
Towards Poisoning the Neural Collaborative Filtering-Based Recommender Systems. ESORICS (1) (2020)
Suresh K. Choubey, Ryan G. Benton, Tom Johnsten
Prescriptive Equipment Maintenance: A Framework. IEEE BigData (2019)
Tom Johnsten, Wyatt Green, Lowell Crook, Ho Yin Chan, Ryan G. Benton, David M. Bourrie
Discovery of Action Rules for Continuously Valued Data. CogMI (2019)
Colby Parker, Jeffrey Todd McDonald, Tom Johnsten, Ryan G. Benton
Android Malware Detection Using Step-Size Based Multi-layered Vector Space Models. MALWARE (2018)
Grant Daly, Ryan Benton, Tom Johnsten
A Multi-Objective Evolutionary Action Rule Mining Method. CEC (2018)
Tom Johnsten, Laura Fain, Leanna Fain, Ryan G. Benton, Ethan Butler, Lewis Pannell, Ming Tan
Exploiting multi-layered vector spaces for signal peptide detection. Int. J. Data Min. Bioinform. 13 (2) (2015)
Tom Johnsten, Samy Alihamad, Ashwin Kannalath, Ryan G. Benton
Targeted Action Rule Discovery. ICMLA (1) (2013)
Vijay V. Raghavan, Ryan G. Benton, Tom Johnsten, Ying Xie
Representations for Large-Scale Sequence Data Mining: A Tale of Two Vector Space Models. RSFDGrC (2013)
Ryan G. Benton, Suresh K. Choubey, David G. Clark, Tom Johnsten, Vijay V. Raghavan
Diagnosis and Grading of Alzheimer's Disease via Automatic Classification of FDG-PET Scans. Brain and Health Informatics (2013)
Ying Xie, Jonathan Fisher, Vijay V. Raghavan, Tom Johnsten, Can Akkoç
Granular Approach for Protein Sequence Analysis. RSCTC (2012)
Jeffrey P. Landry, John Harold Pardue, Tom Johnsten, Matt Campbell, Priya Patidar
A Threat Tree for Health Information Security and Privacy. AMCIS (2011)
Can Akkoç, Tom Johnsten, Ryan G. Benton
Multi-layered Vector Spaces for Classifying and Analyzing Biological Sequences. BICoB (2011)
Raj Singh, Tom Johnsten, Vijay V. Raghavan, Ying Xie
Algorithms for discovering potentially interesting patterns. Int. J. Granul. Comput. Rough Sets Intell. Syst. 2 (2) (2011)
Djellel Eddine Difallah, Ryan G. Benton, Vijay V. Raghavan, Tom Johnsten
FAARM: Frequent Association Action Rules Mining Using FP-Tree. ICDM Workshops (2011)
Raj Singh, Tom Johnsten, Vijay V. Raghavan, Ying Xie
Efficient Algorithm for Discovering Potential Interesting Patterns with Closed Itemsets. GrC (2010)
Raj Singh, Tom Johnsten, Vijay V. Raghavan, Ying Xie
An efficient algorithm for discovering positive and negative patterns. GrC (2009)
Ying Xie, Tom Johnsten, Vijay V. Raghavan, Karthik Ramachandran
On discovering "potentially useful" patterns from databases. GrC (2006)
Tom Johnsten, Robert B. Sweeney, Vijay V. Raghavan
A Methodology for Hiding Knowledge in XML Document Collections. COMPSAC (2003)
Tom Johnsten, Vijay V. Raghavan, Kevin Hill
On Security and Privacy Risks in Association Mining Algorithms. DBSec (2002)
Tom Johnsten, Vijay V. Raghavan
Security Procedures for Classification Mining Algorithms. DBSec (2001)
Tom Johnsten, Vijay V. Raghavan
Impact of Decision-Region Based Classification Mining Algorithms on Database Security. DBSec (1999)