Search Results for author: Sotiris K. Tasoulis

Found 6 papers, 3 papers with code

Detection of Fake Generated Scientific Abstracts

1 code implementation12 Apr 2023 Panagiotis C. Theocharopoulos, Panagiotis Anagnostou, Anastasia Tsoukala, Spiros V. Georgakopoulos, Sotiris K. Tasoulis, Vassilis P. Plagianakos

The widespread adoption of Large Language Models and publicly available ChatGPT has marked a significant turning point in the integration of Artificial Intelligence into people's everyday lives.

Text Classification

Approximate kNN Classification for Biomedical Data

no code implementations3 Dec 2020 Panagiotis Anagnostou, Petros T. Barmbas, Aristidis G. Vrahatis, Sotiris K. Tasoulis

Regarding the classification process for scRNA-seq data, an appropriate method is the k Nearest Neighbor (kNN) classifier since it is usually utilized for large-scale prediction tasks due to its simplicity, minimal parameterization, and model-free nature.

Classification General Classification

Real Time Sentiment Change Detection of Twitter Data Streams

no code implementations2 Apr 2018 Sotiris K. Tasoulis, Aristidis G. Vrahatis, Spiros V. Georgakopoulos, Vassilis P. Plagianakos

Given the fact that Twitter messages are generated constantly with dizzying rates, a huge volume of streaming data is created, thus there is an imperative need for accurate methods for knowledge discovery and mining of this information.

Change Detection Twitter Sentiment Analysis

Convolutional Neural Networks for Toxic Comment Classification

1 code implementation27 Feb 2018 Spiros V. Georgakopoulos, Sotiris K. Tasoulis, Aristidis G. Vrahatis, Vassilis P. Plagianakos

To justify this decision we choose to compare CNNs against the traditional bag-of-words approach for text analysis combined with a selection of algorithms proven to be very effective in text classification.

Cloud Computing General Classification +3

Minimum Density Hyperplanes

no code implementations15 Jul 2015 Nicos G. Pavlidis, David P. Hofmeyr, Sotiris K. Tasoulis

Associating distinct groups of objects (clusters) with contiguous regions of high probability density (high-density clusters), is central to many statistical and machine learning approaches to the classification of unlabelled data.

Classification Clustering +1

Cannot find the paper you are looking for? You can Submit a new open access paper.