Joseph D. Prusa

According to our database1, Joseph D. Prusa authored at least 27 papers between 2015 and 2019.

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

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Other 

Links

On csauthors.net:

Bibliography

2019
Extracting Knowledge from Technical Reports for the Valuation of West Texas Intermediate Crude Oil Futures.
Inf. Syst. Frontiers, 2019

Investigation of Maxout Activations on Convolutional Neural Networks for Big Data Text Sentiment Analysis.
Proceedings of the Thirty-Second International Florida Artificial Intelligence Research Society Conference, 2019

2018
Enhancement of Deep Neural Networks and Their Application to Text Mining.
PhD thesis, 2018

Social media for polling and predicting United States election outcome.
Soc. Netw. Anal. Min., 2018

Location-Based Twitter Sentiment Analysis for Predicting the U.S. 2016 Presidential Election.
Proceedings of the Thirty-First International Florida Artificial Intelligence Research Society Conference, 2018

The Impact of Malicious Accounts on Political Tweet Sentiment.
Proceedings of the 4th IEEE International Conference on Collaboration and Internet Computing, 2018

2017
Improving detection of untrustworthy online reviews using ensemble learners combined with feature selection.
Soc. Netw. Anal. Min., 2017

Improving deep neural network design with new text data representations.
J. Big Data, 2017

Extracting Knowledge from Technical Reports for the Valuation of West Texas Intermediate Crude Oil Futures.
Proceedings of the 2017 IEEE International Conference on Information Reuse and Integration, 2017

Training Convolutional Networks on Truncated Text.
Proceedings of the 29th IEEE International Conference on Tools with Artificial Intelligence, 2017

Deep Neural Network Architecture for Character-Level Learning on Short Text.
Proceedings of the Thirtieth International Florida Artificial Intelligence Research Society Conference, 2017

Exploring the Effectiveness of Twitter at Polling the United States 2016 Presidential Election.
Proceedings of the 3rd IEEE International Conference on Collaboration and Internet Computing, 2017

2016
Designing a Better Data Representation for Deep Neural Networks and Text Classification.
Proceedings of the 17th IEEE International Conference on Information Reuse and Integration, 2016

Cross-Domain Sentiment Analysis: An Empirical Investigation.
Proceedings of the 17th IEEE International Conference on Information Reuse and Integration, 2016

An Investigation of Ensemble Techniques for Detection of Spam Reviews.
Proceedings of the 15th IEEE International Conference on Machine Learning and Applications, 2016

Enhancing Ensemble Learners with Data Sampling on High-Dimensional Imbalanced Tweet Sentiment Data.
Proceedings of the Twenty-Ninth International Florida Artificial Intelligence Research Society Conference, 2016

Necessity of Feature Selection when Augmenting Tweet Sentiment Feature Spaces with Emoticons.
Proceedings of the Twenty-Ninth International Florida Artificial Intelligence Research Society Conference, 2016

Comparing Approaches for Combining Data Sampling and Feature Selection to Address Key Data Quality Issues in Tweet Sentiment Analysis.
Proceedings of the Twenty-Ninth International Florida Artificial Intelligence Research Society Conference, 2016

Reducing Feature Set Explosion to Facilitate Real-World Review Spam Detection.
Proceedings of the Twenty-Ninth International Florida Artificial Intelligence Research Society Conference, 2016

Integrating Multiple Data Sources to Enhance Sentiment Prediction.
Proceedings of the 2nd IEEE International Conference on Collaboration and Internet Computing, 2016

2015
Survey of review spam detection using machine learning techniques.
J. Big Data, 2015

Using Random Undersampling to Alleviate Class Imbalance on Tweet Sentiment Data.
Proceedings of the 2015 IEEE International Conference on Information Reuse and Integration, 2015

Using Ensemble Learners to Improve Classifier Performance on Tweet Sentiment Data.
Proceedings of the 2015 IEEE International Conference on Information Reuse and Integration, 2015

Using Feature Selection in Combination with Ensemble Learning Techniques to Improve Tweet Sentiment Classification Performance.
Proceedings of the 27th IEEE International Conference on Tools with Artificial Intelligence, 2015

The Effect of Dataset Size on Training Tweet Sentiment Classifiers.
Proceedings of the 14th IEEE International Conference on Machine Learning and Applications, 2015

Utilizing Ensemble, Data Sampling and Feature Selection Techniques for Improving Classification Performance on Tweet Sentiment Data.
Proceedings of the 14th IEEE International Conference on Machine Learning and Applications, 2015

Impact of Feature Selection Techniques for Tweet Sentiment Classification.
Proceedings of the Twenty-Eighth International Florida Artificial Intelligence Research Society Conference, 2015


  Loading...