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Outputs (23)

A Deep Learning Approach for Paragraph-Level Paraphrase Generation for Plagiarism Detection (2025)
Journal Article
Saqaabi, A. A., Stewart, C., Akrida, E., & Cristea, A. I. (2025). A Deep Learning Approach for Paragraph-Level Paraphrase Generation for Plagiarism Detection. Neural Processing Letters, 57, 59. https://doi.org/10.1007/s11063-025-11771-9

Expressing information in different forms is an important skill that students should develop in school. This skill positively impacts academic reading and writing. However, it can also lead to negative consequences, such as plagiarism. Students may p... Read More about A Deep Learning Approach for Paragraph-Level Paraphrase Generation for Plagiarism Detection.

A Pedagogical Framework for Developing Abstraction Skills (2025)
Presentation / Conference Contribution
Begum, M., Crossley, J., Strömbäck, F., Akrida, E., Alpizar-Chacon, I., Evans, A., Gross, J. B., Haglund, P., Lonati, V., Satyavolu, C., & Thorgeirsson, S. (2024, July). A Pedagogical Framework for Developing Abstraction Skills. Presented at Annual Conference on Innovation and Technology in Computer Science Education, ITiCSE, Milan, Italy

Abstraction is a fundamental yet challenging skill to teach and learn in Computer Science education. Traditional frameworks of abstraction and concept formation often emphasize understanding an abstraction over its application, the latter being criti... Read More about A Pedagogical Framework for Developing Abstraction Skills.

Designing a Pedagogical Framework for Developing Abstraction Skills (2024)
Presentation / Conference Contribution
Begum, M., Crossley, J., Strömbäck, F., Akrida, E., Alpizar-Chacon, I., Evans, A., Gross, J. B., Haglund, P., Lonati, V., Satyavolu, C., & Thorgeirsson, S. (2024, July). Designing a Pedagogical Framework for Developing Abstraction Skills. Presented at ITiCSE 2024: Innovation and Technology in Computer Science Education, Milan Italy

Paraphrase Generation and Identification at Paragraph-Level (2024)
Presentation / Conference Contribution
Al Saqaabi, A., Stewart, C., Akrida, E., & Cristea, A. I. (2024, June). Paraphrase Generation and Identification at Paragraph-Level. Presented at Generative Intelligence and Intelligent Tutoring Systems ITS 2024, Thessaloniki, Greece

A Paraphrase Identification Approach in Paragraph Length Texts (2023)
Presentation / Conference Contribution
Saqaabi, A. A., Akrida, E., Cristea, A., & Stewart, C. (2022, November). A Paraphrase Identification Approach in Paragraph Length Texts. Presented at IEEE International Conference on Data Mining Workshops Icdmw, Orlando, FL, USA

Measuring the semantic similarity of natural language is a fundamental issue in many tasks, such as paraphrase identification (PI) and plagiarism detection (PD) which are intended to solve maj or issues in education. Various approaches that have been... Read More about A Paraphrase Identification Approach in Paragraph Length Texts.

Narrowing and Stretching: Addressing the Challenge of Multi-track Programming (2022)
Presentation / Conference Contribution
Bradley, S., & Akrida, E. (2022, December). Narrowing and Stretching: Addressing the Challenge of Multi-track Programming. Presented at Computing Education Practice 2022, Durham, England

Given the different amount of programming experience that students have arriving at university, some universities have introduced alternative multiple streams to teach programming. This approach was exemplified by Harvey Mudd College, who successfull... Read More about Narrowing and Stretching: Addressing the Challenge of Multi-track Programming.

Connected Subgraph Defense Games (2021)
Journal Article
Akrida, E. C., Deligkas, A., Melissourgos, T., & Spirakis, P. G. (2021). Connected Subgraph Defense Games. Algorithmica, 83(11), 3403-3431. https://doi.org/10.1007/s00453-021-00858-z

We study a security game over a network played between a defender and k attackers. Every attacker chooses, probabilistically, a node of the network to damage. The defender chooses, probabilistically as well, a connected induced subgraph of the networ... Read More about Connected Subgraph Defense Games.

The temporal explorer who returns to the base (2021)
Journal Article
Akrida, E., Mertzios, G., Spirakis, P., & Raptopoulos, C. (2021). The temporal explorer who returns to the base. Journal of Computer and System Sciences, 120, 179-193. https://doi.org/10.1016/j.jcss.2021.04.001

We study here the problem of exploring a temporal graph when the underlying graph is a star. The aim of the exploration problem in a temporal star is finding a temporal walk which starts and finishes at the center of the star, and visits all leaves.... Read More about The temporal explorer who returns to the base.

How fast can we reach a target vertex in stochastic temporal graphs? (2020)
Journal Article
Akrida, E. C., Mertzios, G. B., Nikoletseas, S., Raptopoulos, C., Spirakis, P. G., & Zmaraev, V. (2020). How fast can we reach a target vertex in stochastic temporal graphs?. Journal of Computer and System Sciences, 114, 65-83. https://doi.org/10.1016/j.jcss.2020.05.005

Temporal graphs abstractly model real-life inherently dynamic networks. Given a graph G, a temporal graph with G as the underlying graph is a sequence of subgraphs (snapshots) of G, where . In this paper we study stochastic temporal graphs, i.e. stoc... Read More about How fast can we reach a target vertex in stochastic temporal graphs?.