SemEval-2017 task 3: Community question answering

P Nakov, D Hoogeveen, L Màrquez, A Moschitti… - arxiv preprint arxiv …, 2019 - arxiv.org
We describe SemEval-2017 Task 3 on Community Question Answering. This year, we reran
the four subtasks from SemEval-2016:(A) Question-Comment Similarity,(B) Question …

Breast cancer prognosis using a machine learning approach

P Ferroni, FM Zanzotto, S Riondino, N Scarpato… - Cancers, 2019 - mdpi.com
Machine learning (ML) has been recently introduced to develop prognostic classification
models that can be used to predict outcomes in individual cancer patients. Here, we report …

Kelp at semeval-2016 task 3: Learning semantic relations between questions and answers

S Filice, D Croce, A Moschitti, R Basili - SemEval 2016-10th …, 2016 - iris.unitn.it
This paper describes the KeLP system par-ticipating in the SemEval-2016 Community
Question Answering (cQA) task. The chal-lenge tasks are modeled as binary classifi-cation …

Risk assessment for venous thromboembolism in chemotherapy-treated ambulatory cancer patients: a machine learning approach

P Ferroni, FM Zanzotto, N Scarpato… - Medical Decision …, 2017 - journals.sagepub.com
Objective. To design a precision medicine approach aimed at exploiting significant patterns
in data, in order to produce venous thromboembolism (VTE) risk predictors for cancer …

[PDF][PDF] Convkn at semeval-2016 task 3: Answer and question selection for question answering on arabic and english fora

A Barrón-Cedeno, D Bonadiman… - Proceedings of the …, 2016 - aclanthology.org
We describe our system, ConvKN, participating to the SemEval-2016 Task 3 “Community
Question Answering”. The task targeted the reranking of questions and comments in real-life …

Kelp at semeval-2017 task 3: Learning pairwise patterns in community question answering

S Filice, G Da San Martino… - Proceedings of the 11th …, 2017 - aclanthology.org
This paper describes the KeLP system participating in the SemEval-2017 community
Question Answering (cQA) task. The system is a refinement of the kernel-based sentence …

[HTML][HTML] Grounded language interpretation of robotic commands through structured learning

A Vanzo, D Croce, E Bastianelli, R Basili, D Nardi - Artificial Intelligence, 2020 - Elsevier
The presence of robots in everyday life is increasing day by day at a growing pace. Industrial
and working environments, health-care assistance in public or domestic areas can benefit …

Exploiting graph kernels for high performance biomedical relation extraction

NC Panyam, K Verspoor, T Cohn… - Journal of biomedical …, 2018 - Springer
Background Relation extraction from biomedical publications is an important task in the area
of semantic mining of text. Kernel methods for supervised relation extraction are often …

[HTML][HTML] Machine learning approach to predict medication overuse in migraine patients

P Ferroni, FM Zanzotto, N Scarpato, A Spila… - Computational and …, 2020 - Elsevier
Abstract Machine learning (ML) is largely used to develop automatic predictors in migraine
classification but automatic predictors for medication overuse (MO) in migraine are still in …

Language processing and learning models for community question answering in Arabic

S Romeo, G Da San Martino, Y Belinkov… - Information Processing …, 2019 - Elsevier
In this paper we focus on the problem of question ranking in community question answering
(cQA) forums in Arabic. We address the task with machine learning algorithms using …