Ioannis Kakadiaris

Also published as: Ioannis A. Kakadiaris


2021

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A Case Study of Deep Learning-Based Multi-Modal Methods for Labeling the Presence of Questionable Content in Movie Trailers
Mahsa Shafaei | Christos Smailis | Ioannis Kakadiaris | Thamar Solorio
Proceedings of the International Conference on Recent Advances in Natural Language Processing (RANLP 2021)

In this work, we explore different approaches to combine modalities for the problem of automated age-suitability rating of movie trailers. First, we introduce a new dataset containing videos of movie trailers in English downloaded from IMDB and YouTube, along with their corresponding age-suitability rating labels. Secondly, we propose a multi-modal deep learning pipeline addressing the movie trailer age suitability rating problem. This is the first attempt to combine video, audio, and speech information for this problem, and our experimental results show that multi-modal approaches significantly outperform the best mono and bimodal models in this task.

2018

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Proceedings of the 6th BioASQ Workshop A challenge on large-scale biomedical semantic indexing and question answering
Ioannis A. Kakadiaris | George Paliouras | Anastasia Krithara
Proceedings of the 6th BioASQ Workshop A challenge on large-scale biomedical semantic indexing and question answering

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Results of the sixth edition of the BioASQ Challenge
Anastasios Nentidis | Anastasia Krithara | Konstantinos Bougiatiotis | Georgios Paliouras | Ioannis Kakadiaris
Proceedings of the 6th BioASQ Workshop A challenge on large-scale biomedical semantic indexing and question answering

This paper presents the results of the sixth edition of the BioASQ challenge. The BioASQ challenge aims at the promotion of systems and methodologies through the organization of a challenge on two tasks: semantic indexing and question answering. In total, 26 teams with more than 90 systems participated in this year’s challenge. As in previous years, the best systems were able to outperform the strong baselines. This suggests that state-of-the-art systems are continuously improving, pushing the frontier of research.

2017

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Results of the fifth edition of the BioASQ Challenge
Anastasios Nentidis | Konstantinos Bougiatiotis | Anastasia Krithara | Georgios Paliouras | Ioannis Kakadiaris
BioNLP 2017

The goal of the BioASQ challenge is to engage researchers into creating cuttingedge biomedical information systems. Specifically, it aims at the promotion of systems and methodologies that are able to deal with a plethora of different tasks in the biomedical domain. This is achieved through the organization of challenges. The fifth challenge consisted of three tasks: semantic indexing, question answering and a new task on information extraction. In total, 29 teams with more than 95 systems participated in the challenge. Overall, as in previous years, the best systems were able to outperform the strong baselines. This suggests that state-of-the art systems are continuously improving, pushing the frontier of research.

2016

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Proceedings of the Fourth BioASQ workshop
Ioannis A. Kakadiaris | George Paliouras | Anastasia Krithara
Proceedings of the Fourth BioASQ workshop

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Results of the 4th edition of BioASQ Challenge
Anastasia Krithara | Anastasios Nentidis | Georgios Paliouras | Ioannis Kakadiaris
Proceedings of the Fourth BioASQ workshop