Recent Submissions

  • Social impact assessment of scientist from mainstream news and weblogs 

    Timilsina, Mohan; Khawaja, Waqas; Davis, Brian; Taylor, Mike; Hayes, Conor (Springer Verlag, 2017-10-14)
    Research policy makers, funding agencies, universities and government organizations evaluate research output or impact based on the traditional citation count, peer review, h-index and journal impact factors. These impact ...
  • Predicting citations from mainstream news, weblogs and discussion forum 

    Timilsina, Mohan; Davis, Brian; Taylor, Mike; Hayes, Conor (ACM (Association for Computing Machinery), 2017-08-23)
    The growth in the alternative digital publishing is widening the breadth of scholarly impact beyond the conventional bibliometric community. Thus, research is becoming more reachable both inside and outside of academic ...
  • Towards predicting academic impact from mainstream news and weblogs: A heterogeneous graph based approach 

    Timilsina, Mohan; Davis, Brian; Taylor, Mike; Hayes, Conor (IEEE, 2016-11-24)
    The realization that scholarly publications are discussed and have influence on discourse outside scientific and academic domains has given rise to area of scientometrics called alternative metrics or “altmetrics”. ...
  • SemEval-2017 Task 5: Fine-grained sentiment analysis on financial microblogs and news 

    Cortis, Keith; Freitas, André; Daudert, Tobias; Huerlimann, Manuela; Zarrouk, Manel; Handschuh, Siegfried; Davis, Brian (Association for Computational Linguistics, 2017-08-03)
    This paper discusses the “Fine-Grained Sentiment Analysis on Financial Microblogs and News” task as part of SemEval-2017, specifically under the “Detecting sentiment, humour, and truth” theme. This task contains two ...
  • 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, ...
  • A case study of collecting dynamic social data: The pro-ana twitter community 

    Wood, Ian (Australian National University, College of Engineering and Computer Science, Department of Computer Science, 2015)
    The study of social processes in on-line social media content is a relatively new and rapidly growing endeavour. Many social media platforms provide a public API (Application Programming Interface) which can be used for ...
  • 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 ...
  • Improved edge detection algorithm for brain tumor segmentation 

    Aslam, Asra; Khan, Ekram; Beg, M.M. Sufyan (Elsevier, 2015-08-21)
    Image segmentation is used to separate objects from the background, and thus it has proved to be a powerful tool in bio-medical imaging. In this paper, an Improved Edge Detection algorithm for brain-tumor segmentation is ...

View more