338 citations · 698 across the 54 of their papers we have counts for
8 papers · 1 filter
Drug-Target Interaction Prediction via an Ensemble of Weighted Nearest Neighbors with Interaction Recovery
Bin Liu, Konstantinos Pliakos, Celine Vens +1
Predicting drug-target interactions (DTI) via reliable computational methods is an effective and efficient way to mitigate the enormous costs and time of the drug discovery process…
From Protocol to Screening: A Hybrid Learning Approach for Technology-Assisted Systematic Literature Reviews
Athanasios Lagopoulos, Grigorios Tsoumakas
In the medical domain, a Systematic Literature Review (SLR) attempts to collect all empirical evidence, that fit pre-specified eligibility criteria, in order to answer a specific r…
Altruist: Argumentative Explanations through Local Interpretations of Predictive Models
Ioannis Mollas, Nick Bassiliades, Grigorios Tsoumakas
Explainable AI is an emerging field providing solutions for acquiring insights into automated systems' rationale. It has been put on the AI map by suggesting ways to tackle key eth…
Keywords lie far from the mean of all words in local vector space
Eirini Papagiannopoulou, Grigorios Tsoumakas, Apostolos N. Papadopoulos
Keyword extraction is an important document process that aims at finding a small set of terms that concisely describe a document's topics. The most popular state-of-the-art unsuper…
ETHOS: an Online Hate Speech Detection Dataset
Ioannis Mollas, Zoe Chrysopoulou, Stamatis Karlos +1
Online hate speech is a recent problem in our society that is rising at a steady pace by leveraging the vulnerabilities of the corresponding regimes that characterise most social m…
Multi-Label Sampling based on Local Label Imbalance
Bin Liu, Konstantinos Blekas, Grigorios Tsoumakas
Class imbalance is an inherent characteristic of multi-label data that hinders most multi-label learning methods. One efficient and flexible strategy to deal with this problem is t…
Beyond MeSH: Fine-Grained Semantic Indexing of Biomedical Literature based on Weak Supervision
Anastasios Nentidis, Anastasia Krithara, Grigorios Tsoumakas +1
In this work, we propose a method for the automated refinement of subject annotations in biomedical literature at the level of concepts. Semantic indexing and search of biomedical…
A Divide-and-Conquer Approach to the Summarization of Long Documents
Alexios Gidiotis, Grigorios Tsoumakas
We present a novel divide-and-conquer method for the neural summarization of long documents. Our method exploits the discourse structure of the document and uses sentence similarit…