1 code implementation • 20 Jan 2022 • Erasmo Artur, Rosane Minghim
Multidimensional data analysis has become increasingly important in many fields, mainly due to current vast data availability and the increasing demand to extract knowledge from it.
no code implementations • COLING 2016 • Anh Dang, Abidalrahman Moh{'}d, Aminul Islam, Rosane Minghim, Michael Smit, Evangelos Milios
This paper introduces a new large-scale n-gram corpus that is created specifically from social media text.
no code implementations • 14 Dec 2020 • Sonia Castelo, Moacir Ponti, Rosane Minghim
Multiple-instance learning (MIL) is a paradigm of machine learning that aims to classify a set (bag) of objects (instances), assigning labels only to the bags.
no code implementations • 12 Jul 2022 • Haseeb Younis, Paul Trust, Rosane Minghim
The results, supported by illustrative methods of the processes of LSP and t-SNE, are meant to inspire students in understanding the mathematics behind such methods, in order to apply them in effective data analysis tasks in multiple applications.
no code implementations • 10 Aug 2022 • Paul Trust, Ahmed Zahran, Rosane Minghim
The need for timely data analysis for economic decisions has prompted most economists and policy makers to search for non-traditional supplementary sources of data.
no code implementations • COLING (TextGraphs) 2022 • Paul Trust, Provia Kadusabe, Haseeb Younis, Rosane Minghim, Evangelos Milios, Ahmed Zahran
This paper describes our system for the submission to the TextGraphs 2022 shared task at COLING 2022: Natural Language Premise Selection (NLPS) from mathematical texts.
no code implementations • SMM4H (COLING) 2022 • Paul Trust, Provia Kadusabe, Ahmed Zahran, Rosane Minghim, Kizito Omala
The paper describes our submissions for the Social Media Mining for Health (SMM4H) workshop 2022 shared tasks.