In this study, we propose a new method to predict the effectiveness of an intervention in a clinical trial.
We, therefore, introduce XBRL tagging as a new entity extraction task for the financial domain and release FiNER-139, a dataset of 1. 1M sentences with gold XBRL tags.
A focused crawler aims at discovering as many web pages relevant to a target topic as possible, while avoiding irrelevant ones; i. e. maximizing the harvest rate.
We show how SRA can be used in Complex Event Recognition in order to detect patterns upon streams of events, using our framework that provides declarative and compositional semantics, and that allows for a systematic treatment of such automata.
Black-box decision models have been widely adopted both in industry and academia due to their excellent performance across many challenging tasks and domains.
In particular, prediction suffix trees, being variable-order Markov models, have the ability to capture long-term dependencies in a stream by remembering only those past sequences that are informative enough.
Advancing the state-of-the-art in large-scale biomedical semantic indexing and question answering is the main focus of the BioASQ challenge.
In this paper, we present an overview of the eighth edition of the BioASQ challenge, which ran as a lab in the Conference and Labs of the Evaluation Forum (CLEF) 2020.
In this document, we report an analysis of the Public MeSH Note field of the new descriptors introduced in the MeSH thesaurus between 2006 and 2020.
Complex Event Recognition (CER) systems detect event occurrences in streaming time-stamped input using predefined event patterns.
1 code implementation • 25 Mar 2021 • Charilaos Akasiadis, Miguel Ponce-de-Leon, Arnau Montagud, Evangelos Michelioudakis, Alexia Atsidakou, Elias Alevizos, Alexander Artikis, Alfonso Valencia, Georgios Paliouras
The main challenges are first to calibrate the simulators so as to reproduce real-world cases, and second, to search for specific values of the parameter space concerning effective drug treatments.
To this end, we propose a framework to categorize new descriptors based on their current relation to older descriptors.
The results of the seventh edition of the BioASQ challenge are presented in this paper.
To this end, we propose a new method that uses weak supervision to train a concept annotator on the literature available for a particular disease.
In biomedical research, unified access to up-to-date domain-specific knowledge is crucial, as such knowledge is continuously accumulated in scientific literature and structured resources.
As the detection of fake news is increasingly considered a technological problem, it has attracted considerable research.
This paper proposes a method to guide tensor factorization, using class labels.
This paper presents the results of the sixth edition of the BioASQ challenge.
Online structure learning approaches, such as those stemming from Statistical Relational Learning, enable the discovery of complex relations in noisy data streams.
The Complex Event Recognition (CER) group is a research team, affiliated with the National Centre of Scientific Research "Demokritos" in Greece.
The goal of the BioASQ challenge is to engage researchers into creating cuttingedge biomedical information systems.
Logic-based event recognition systems infer occurrences of events in time using a set of event definitions in the form of first-order rules.
no code implementations • 8 Mar 2017 • Alain Kibangou, Alexander Artikis, Evangelos Michelioudakis, Georgios Paliouras, Marius Schmitt, John Lygeros, Chris Baber, Natan Morar, Fabiana Fournier, Inna Skarbovsky
Traffic on freeways can be managed by means of ramp meters from Road Traffic Control rooms.
The Event Calculus is a temporal logic that has been used as a basis in event recognition applications, providing among others, direct connections to machine learning, via Inductive Logic Programming (ILP).
Systems for symbolic event recognition accept as input a stream of time-stamped events from sensors and other computational devices, and seek to identify high-level composite events, collections of events that satisfy some pattern.
Hierarchical classification addresses the problem of classifying items into a hierarchy of classes.
In a typical event recognition application, however, these systems often have to deal with a significant amount of uncertainty.
The input of our system is a set of time-stamped short-term activities (STA) detected on video frames.