Recent Submissions

  • Accurate Bayesian prediction of cardiovascular-related mortality using ambulatory blood pressure measurements 

    O'Neill, James; Madden, Michael G.; Dolan, Eamon (Springer Cham, 2017-05-30)
    Hypertension is the leading cause of cardiovascular-related mortality (CVRM), affecting approximately 1 billion people worldwide. To enable patients at significant risk of CVRM to be treated appropriately, it is essential ...
  • Regularizing knowledge graph embeddings via equivalence and inversion axioms 

    Minervini, Pasquale; Costabello, Luca; Muñoz, Emir; Nováček, Vít; Vandenbussche, Pierre-Yves (Springer Verlag, 2017-12-30)
    Learning embeddings of entities and relations using neural architectures is an effective method of performing statistical learning on large-scale relational data, such as knowledge graphs. In this paper, we consider the ...
  • Random indexing revisited 

    QasemiZadeh, Behrang (Springer, 2015-05-17)
    Random indexing is a method for constructing vector spaces at a reduced dimensionality. Previously, the method has been proposed using Kanerva's sparse distributed memory model. Although intuitively plausible, this ...
  • Multimodal emotion recognition for AVEC 2016 challenge 

    Povolny, Filip; Matejka, Pavel; Hradis, Michal; Popkova, Anna; Otrusina, Lubomir; Smrz, Pavel; Wood, Ian; Robin, Cecile; Lamel, Lori (ACM, 2016-10-16)
    This paper describes a systems for emotion recognition and its application on the dataset from the AV+EC 2016 Emotion Recognition Challenge. The realized system was produced and submitted to the AV+EC 2016 evaluation, ...
  • NUIG at EmoInt-2017: BiLSTM and SVR ensemble to detect emotion intensity 

    Andryushechkin, Vladimir; Wood, Ian; O'Neill, James (Association for Computational Linguistics, 2017-09-08)
    This paper describes the entry NUIG in the WASSA 20171 shared task on emotion recognition. The NUIG system used an SVR (SVM regression) and BiLSTM ensemble, utilizing primarily n-grams (for SVR features) and tweet word ...
  • PandemCap: decision support tool for epidemic management 

    Yañez, Andrea; Duggan, James; Jilani, Musfira; Connolly, Maire; Hayes, Conor (NUI Galway, 2017-10-01)
    Pandemics or high impact epidemics are one of the biggest threats facing humanity today. While a complete elimination of the occurrence of such threats is improbable, it is possible to contain their impact by efficient ...
  • The path to success: A study of user behaviour and success criteria in online communities 

    Aumayr, Erik; Hayes, Conor (ACM, 2017-08-23)
    Maintaining online communities is vital in order to increase and retain their economic and social value. That is why community managers look to gauge the success of their communities by measuring a variety of user behaviour, ...
  • The role of open data in driving sustainable mobility in nine smart cities 

    Yadav, Piyush; Hasan, Souleiman; Ojo, Adegboyega; Curry, Edward (Association for Information Systems, 2017-06-05)
    In today’s era of globalization, sustainable mobility is considered as a key factor in the economic growth of any country. With the emergence of open data initiatives, there is tremendous potential to improve mobility. ...
  • Multi-threading based implementation of ant-colony optimization algorithm for image edge detection 

    Aslam, Asra; Khan, Ekram; Beg, M.M. Sufyan (IEEE, 2015-10-17)
    Ant Colony Optimization (ACO) is a nature inspired algorithm for solving optimization problems and is proved to be a powerfnl tool in image processing. It works on the principle that an ant while moving leaves pheromones ...
  • Non-partitioning merge-sort: Performance enhancement by elimination of division in divide-and-conquer algorithm 

    Aslam, Asra; Ansari, Mohd. Samar; Varshney, Shikha (ACM, 2016-03-04)
    The importance of a high performance sorting algorithm with low time complexity cannot be over stated. Several benchmark algorithms viz. Bubble Sort, Insertion Sort, Quick Sort, and Merge Sort, etc. have tried to achieve ...
  • Analysing and improving embedded markup of learning resources on the web 

    Dietze, Stefan; Taibi, Davide; Yu, Ran; Barker, Phil; d'Aquin, Mathieu (ACM, 2017-04-03)
    Web-scale reuse and interoperability of learning resources have been major concerns for the technology-enhanced learning community. While work in this area traditionally focused on learning resource metadata, provided ...
  • Unsupervised learning for understanding student achievement in a distance learning setting 

    Liu, Shuangyan; d'Aquin, Mathieu (IEEE, 2017-04-25)
    Many factors could affect the achievement of students in distance learning settings. Internal factors such as age, gender, previous education level and engagement in online learning activities can play an important role ...
  • Measuring accuracy of triples in knowledge graphs 

    Liu, Shuangyan; d'Aquin, Mathieu; Motta, Enrico (Springer, 2017-06-19)
    An increasing amount of large-scale knowledge graphs have been constructed in recent years. Those graphs are often created from text-based extraction, which could be very noisy. So far, cleaning knowledge graphs are ...
  • Challenges with image event processing: Poster 

    Aslam, Asra; Hasan, Souleiman; Curry, Edward (ACM, 2017-06-19)
    There has been substantial research in the area of event processing where systems are focused on event processing of structured data. However, in the context of smart cities, signi cant number of realtime applications ...
  • Classifying sentential modality in legal language: A use case in financial regulations, acts and directives 

    O'Neill, James; Buitelaar, Paul; Robin, Cécile; O'Brien, Leona (ACM, 2017-06-12)
    Texts expressed in legal language are often di cult and time consuming for lawyers to read through, particularly for the purpose of identifying relevant deontic modalities (obligations, prohibitions and permissions). ...
  • Using drug similarities for discovery of possible adverse reactions 

    Muñoz, Emir; Nováček, Vít; Vandenbussche, Pierre-Yves (AMIA, 2017-02-10)
    We propose a new computational method for discovery of possible adverse drug reactions. The method consists of two key steps. First we use openly available resources to semi-automatically compile a consolidated data set ...
  • Grand challenge: Automatic anomaly detection over sliding windows 

    Zaarour, Tarek; Pavlopoulou, Niki; Hasan, Souleiman; ul Hassan, Umair; Curry, Edward (Association for Computing Machinery ACM, 2017-06-19)
    With the advances in the Internet of Things and rapid generation of vast amounts of data, there is an ever growing need for leveraging and evaluating event-based systems as a basis for building realtime data analytics ...
  • Mining cardinalities from knowledge bases 

    Muñoz, Emir; Nickles, Matthias (Springer Verlag, 2017-08-01)
    Cardinality is an important structural aspect of data that has not received enough attention in the context of RDF knowledge bases (KBs). Information about cardinalities can be useful for data users and knowledge engineers ...
  • Tell me who are your friends, and I’ll tell you who you are 

    Torres-Tramón, Pablo; Hayes, Conor (AICS 2016, 2016-09-20)
    Mentions of politicians in news articles can reflect politician interactions on their daily activities. In this work, we present a mathematical model to represent such interactions as a graph, and we use it to predict the ...
  • On developing extraction rules for mining informal scientific references from Altmetric data sources 

    Khawaja, Waqas; Taylor, Michael; Davis, Brian (Springer Verlag, 2015-06-04)
    Altmetrics measure scientific impact outside of traditional scientific literature. We identify mentions of scientific research or entities like researchers, academic or research organizations in a corpus containing blogs, ...

View more