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Advanced Computing Systems

At CRACS, our mission is to pursue scientific excellence in the areas of programming languages, parallel and distributed computing, security and privacy, information mining, and Web based systems with a focus on developing scalable software systems for challenging, multidisciplinary applications.

Our research environment is enriched with junior talented researchers that together with senior researchers build the necessary critical mass and scientific competences to fulfill the institution’s mission.

Latest News
Computer Science

INESC TEC organises workshops in the fields of Logic and Verification

Sandra Alves, researcher at INESC TEC’s Centre for Advanced Computing Systems (CRACS), was involved in the organisation of the fourth edition of the Women in Logic (WiL) workshop and the second edition of the Linearity & TLLA workshop.

27th July 2020

Computer Science

INESC TEC uses statistical and psycholinguistic indicators to detect fake news

In early May, the European Commission registered more than 2.700 daily articles with fake news related to covid-19 on social networks, including false or misleading posts. Those responsible for said European body even considered misinformation the “disease of the century”.

26th May 2020

Computer Science

Mobile app meuparlamento.pt among the winners of the World Summit Awards

The phone app meuparlamento.pt is one of the 40 winners of the World Summit Awards, an international competition that elects projects focused on promoting digital innovation at local level.

17th March 2020

Computer Science

INESC TEC researcher wins Best Paper Application in international congress

This award was given under the BLOCKCHAIN 2019 - International Congress on Blockchain and Applications event, which was held in Ávila, Spain between 26 and 28 June.

13th July 2019

Computer Science

New INESC TEC publication on Supporting Tools for Development

Ricardo Queirós, collaborator of INESC TEC’s Centre for Research in Advanced Computing Systems (CRACS) published a new book entitled "Code Generation, Analysis Tools, and Testing for Quality".

18th February 2019

Interest Topics
036

Featured Projects

Cortaderia

Desenvolvimento de Software para Monitorização da Espécie Invasora Cortaderia selloana

2020-2020

Authenticus19_20

Consultoria Tecnológica em Sistemas CRIS e Cálculo de APC

2019-2020

T4CDTKC

Training 4 Cotec, Digital Transformation Knowledge Challenge - Elaboração de Programa de Formação “CONHECER E COMPREENDER O DESAFIO DAS TECNOLOGIAS DE TRANSFORMAÇÃO DIGITAL”

2019-2020

EFA-Cloud

Consultadoria EFACEC

2019-2020

Authenticus2019

Apoio Técnico ao CINTESIS para extração de indicadores de produção científica baseados no Authenticus

2019-2019

Angerona

Privacy preserving IOT middleware

2018-2019

FGPE

Framework for Gamified Programming Education

2018-2021

AuthenticusNF

Desenvolvimento de Indicadores de Produção Científica Baseados no Authenticus

2018-2019

PGODISSEIA

Serviço de instalação e configuração de uma plataforma de autenticação, implementação de solução de gestão centralizada de certificados digitais, auditoria de segurança (pen-testing) e análise de impacto de privacidade dos tratamentos de dados pessoais das plataformas de integração e autenticação

2018-2019

CRADLE

Deep learning in cancer drug discovery: a pipeline for the generation of new therapies

2018-2021

ELVEN

Elven - Expressive Logics for VErifying the Net

2016-2019

Digi-NewB

Non-invasive monitoring of perinatal health through multiparametric digital representation of clinically relevant functions for improving clinical intervention in neonatal units (Digi-NewB)

2016-2020

FOUREYES

TEC4Growth - RL FourEyes - Intelligence, Interaction, Immersion and Innovation for media industries

2015-2019

NanoStima-RL5

NanoSTIMA - Advanced Methodologies for Computer-Aided Detection and Diagnosis

2015-2019

NanoStima-RL3

NanoSTIMA - Health data infrastructure

2015-2019

NanoStima-RL4

NanoSTIMA - Health Data Analysis & Decision

2015-2019

SMILES

SMILES - Smart, Mobile, Intelligent and Large scale Sensing and analytics

2015-2019

FOTOCATGRAF

Graphene-based semiconductor photocatalysis for a safe and sustainable water supply: an advanced technology for emerging pollutants removal

2015-2018

REMINDS

Relevance Mining and Detection System (REMINDS)

2015-2017

PANF

Methods to retrieve and communicate data from Sifarma

2015-2016

SEA

SEA-Sistema de ensino autoadaptativo

2015-2015

MGI

Contrato de Aquisição de serviços de produção e desenvolvimento de módulo para gestão de iterações para integrar no sistema de informação da UP (SIGARRA)

2015-2015

Hyrax

Crowd-Sourcing Mobile Devices to Develop Edge Clouds

2014-2018

DAT

Curation and intelligent data analysis

2014-2015

ABLe

Advice-Based Learning for Health Care

2013-2015

Authenticus

Authenticus - System to Identify and Validate Portuguese Scientific Publications

2013-2016

SIBILA

Towards Smart Interacting Blocks that Improve Learned Advice

2013-2015

ADE

Adverse Drug Effects Detection

2012-2015

e-Policy

Engineering for the Policy-making Life Cycle (ePolicy)

2011-2014

Leap

Logic environments with Advanced Paralelism

2011-2014

MACAW

Macroprogramming for Wireless Sensor Networks

2011-2014

Breadcrumbs

Social network based on personal libraries of news fragments

2010-2012

Ofelia

Open Federated Environments Leveraging Identity and Authorization

2010-2013

Horus

Horn Representations of Uncertain Systems

2010-2013

DIGISCOPE

DIGItally enhanced stethosCOPE for clinical usage

2010-2013

Palco3.0

Intelligent Web system to support the management of a social network on music

2008-2011

Team
Publications

CRACS Publications

View all Publications

2020

Identifying journalistically relevant social media texts using human and automatic methodologies

Authors
Guimaraes, N; Miranda, F; Figueira, A;

Publication
INTERNATIONAL JOURNAL OF GRID AND UTILITY COMPUTING

Abstract
Social networks have provided the means for constant connectivity and fast information dissemination. In addition, real-time posting allows a new form of citizen journalism, where users can report events from a witness perspective. Therefore, information propagates through the network at a faster pace than traditional media reports it. However, relevant information is a small percentage of all the content shared. Our goal is to develop and evaluate models that can automatically detect journalistic relevance. To do it, we need solid and reliable ground truth data with a significantly large quantity of annotated posts, so that the models can learn to detect relevance over all the spectrum. In this article, we present and confront two different methodologies: an automatic and a human approach. Results on a test data set labelled by experts' show that the models trained with automatic methodology tend to perform better in contrast to the ones trained using human annotated data.

2020

Contribution of Social Tagging to Clustering Effectiveness Using as Interpretant the User’s Community

Authors
Cunha, E; Figueira, Á;

Publication
Trends and Innovations in Information Systems and Technologies - Advances in Intelligent Systems and Computing

Abstract

2020

Analysis and Detection of Unreliable Users in Twitter: Two Case Studies

Authors
Guimaraes, N; Figueira, A; Torgo, L;

Publication
Communications in Computer and Information Science - Knowledge Discovery, Knowledge Engineering and Knowledge Management

Abstract

2020

FOCAS: Penalising friendly citations to improve author ranking

Authors
Silva, JMB; Aparício, D; Ribeiro, P; Silva, FMA;

Publication
Proceedings of the ACM Symposium on Applied Computing

Abstract
Scientific impact is commonly associated with the number of citations received. However, an author can easily boost his own citation count by (i) publishing articles that cite his own previous work (self-citations), (ii) having co-authors citing his work (co-author citations), or (iii) exchanging citations with authors from other research groups (reciprocated citations). Even though these friendly citations inflate an author's perceived scientific impact, author ranking algorithms do not normally address them. They, at most, remove self-citations. Here we present Friends-Only Citations AnalySer (FOCAS), a method that identifies friendly citations and reduces their negative effect in author ranking algorithms. FOCAS combines the author citation network with the co-authorship network in order to measure author proximity and penalises citations between friendly authors. FOCAS is general and can be regarded as an independent module applied while running (any) PageRank-like author ranking algorithm. FOCAS can be tuned to use three different criteria, namely authors' distance, citation frequency, and citation recency, or combinations of these. We evaluate and compare FOCAS against eight state-of-the-art author ranking algorithms. We compare their rankings with a ground-truth of best paper awards. We test our hypothesis on a citation and co-authorship network comprised of seven Information Retrieval top-conferences. We observed that FOCAS improved author rankings by 25% on average and, in one case, leads to a gain of 46%. © 2020 ACM.

2020

Jay: Adaptive Computation Offloading for Hybrid Cloud Environments

Authors
Silva, JMA; Marques, ERB; Lopes, LMB; Silva, FMA;

Publication
2020 Fifth International Conference on Fog and Mobile Edge Computing (FMEC)

Abstract

Supervised Theses

2020

Lock-Free Memory Reclamation for Concurrent Hash Tries

Author
Paulo Jorge Teixeira Rosa

Institution
UP-FCUP

2019

Forder application

Author
David Emanuel Torres Mendes

Institution
IPP-ESTG

2019

Generic Lock-Free Memory Reclamation

Author
Pedro Carvalho Moreno

Institution
UP-FCUP

2019

Android Security by Introspection

Author
João Vasco Bispo Estrela

Institution
UP-FCUP

2019

Arquitetura segura no desenvolvimento de software: Abordagem à plataforma digital U.OPENLAB

Author
Domingos Alberto Teixeira Guedes Ferreira

Institution
UP-FCUP

Facts & Figures

16Papers in indexed journals

2019

2Book Chapters

2019

22Proceedings in indexed conferences

2019