Skip To Main Content
Katia Lida Kermanidis on Muck Rack

Katia Lida Kermanidis

As seen in: MDPI
Is this you? As a journalist, you can create a free Muck Rack account to customize your profile, list your contact preferences, and upload a portfolio of your best work. Claim your profile

Get in touch with Katia Lida

Contact Katia Lida, search articles and posts on X, monitor coverage, and track replies from one place.

Learn more about Muck Rack

Actions

Share this page

Is this you?

As a journalist, you can create a free Muck Rack account to customize your profile, list your contact preferences, and upload a portfolio of your best work.
Claim your profile

Articles

From Misinformation to Insight: Machine Learning Strategies for Fake News Detection

|
By Andreas Kanavos, Katia Lida Kermanidis, Despoina Mouratidis
| MDPI
All articles published by MDPI are made immediately available worldwide under an open access license. No special permission is required to reuse all or part of the article published by MDPI, including figures and tables. For articles published under an open access Creative Common CC BY license, any part of the article may be reused without permission provided that the original article is clearly cited. For more information, please refer to https://www.mdpi.com/openaccess.
Open in Who Shared View Duplicates (31) Issue with article?

Exploring the Effectiveness of Shallow and L2 Learner-Suitable Textual Features for Supervised and Unsupervised Sentence-Based Readability Assessment

|
By Dimitris Kostadimas, Katia Lida Kermanidis, Theodore Andronikos, Katia Lida
| MDPI
1. Introduction As globalization continues, an ever-increasing trend of immigration and cultural exchange is observed. Upon arriving in another country, immigrants have to overcome language barriers, along with many other challenges. The degree to which a reader finds a document difficult to understand is measured through readability assessment, a process supported by machine learning and linguistics.
Open in Who Shared Issue with article?

Vocational Domain Identification with Machine Learning and Natural Language Processing on Wikipedia Text: Error Analysis and Class Balancing

|
By Adamantia Pateli, Maria Nefeli Nikiforos, Konstantina Deliveri, Katia Lida Kermanidis
| MDPI
5. Data Balancing Another machine learning experiment on domain identification was performed with a Random Forest (https://docs.rapidminer.com/9.10/studio/operators/modeling/predictive/trees/parallel_random_forest.html, accessed on 20 October 2022) and AdaBoost (https://docs.rapidminer.com/9.1/studio/operators/modeling/predictive/ensembles/adaboost.html, accessed on 20 October 2022) model. The results of this experiment are shown in Table 7.
Open in Who Shared Issue with article?
See all 3 articles