Recent Submissions

  • MixedEmotions: An open-source toolbox for multi-modal emotion analysis 

    Buitelaar, Paul; Wood, Ian D.; Negi, Sapna; Arcan, Mihael; McCrae, John P.; Abele, Andrejs; Robin, Cécile; Andryushechkin, Vladimir; Ziad, Housam; Sagha, Hesam; Schmitt, Maximilian; Schuller, Björn W.; Sánchez-Rada, J. Fernando; Iglesias, Carlos A.; Navarro, Carlos; Giefer, Andreas; Heise, Nicolaus; Masucci, Vincenzo; Danza, Francesco A.; Caterino, Ciro; Smrž, Pavel; Hradiš, Michal; Povolný, Filip; Klimeš, Marek; Matějka, Pavel; Tummarello, Giovanni (IEEE, 2018-01-25)
    Recently, there is an increasing tendency to embed the functionality of recognizing emotions from the user generated contents, to infer richer profile about the users or contents, that can be used for various automated ...
  • Automatic taxonomy generation: a use-case in the legal domain 

    Robin, Cécile; O'Neill, James; Buitelaar, Paul (LTC'17, 8th Language & Technology Conference, 2017-11-17)
    A key challenge in the legal domain is the adaptation and representation of the legal knowledge expressed through texts, in order for legal practitioners and researchers to access this information more easily and faster ...
  • Teanga: a linked data based platform for natural language processing 

    Ziad, Housam; McCrae, John Philip; Buitelaar, Paul (Language Resources and Evaluation Conference (LREC 2018), 2018-05-07)
    In this paper, we describe Teanga, a linked data based platform for natural language processing (NLP). Teanga enables the use of many NLP services from a single interface, whether the need was to use a single service or ...
  • The colloquial WordNet: Extending Princeton WordNet with neologisms 

    McCrae, John P.; Wood, Ian D.; HIcks, Amanda (Springer International Publishing, 2017-05-27)
    Princeton WordNet is one of the most important resources for natural language processing, but has not been updated for over ten years and is not suitable for analyzing the fast moving language as used on social media. We ...
  • Multimodal multimodel emotion analysis as linked data 

    Sánchez-Rada, J. Fernando; Iglesias, Carlos A.; Sagha, Hesam; Schuller, Björn; Ian D. Wood, Ian D.; Buitelaar, Paul (IEEE, 2017-10-23)
    The lack of a standard emotion representation model hinders emotion analysis due to the incompatibility of annotation formats and models from different sources, tools and annotation services. This is also a limiting ...
  • Demonstrating a linked data platform for finite element biosimulations of cochlear mechanics 

    Mehdi, Muntazir; Khan, Yasar; Freitas, Andre; Jares, Joao; Hasapis, Panagiotis; Sahay, Ratnesh (CEUR-WS.org, 2015-10-11)
    Biosimulations employ Finite Element Method (FEM) to simulate complex biological systems in order to understand different aspects of human organs. The applications of FEM biosimulations range from human ear cochlear mechanics, ...
  • Detecting inner-ear anatomical and clinical datasets in the linked open data (LOD) cloud 

    Mehdi, Muntazir; Iqbal, Aftab; Khan, Yasar; Decker, Stefan; Sahay, Ratnesh (CEUR-WS.org, 2015-10-15)
    Linked Open Data (LOD) Cloud is a mesh of open datasets coming from different domains. Among these datasets, a notable amount of datasets belong to the life sciences domain linked together forming an interlinked “Life ...
  • A linked data platform for finite element biosimulations 

    Mehdi, Muntazir; Khan, Yasar; Freitas, Andre; Jares, Joao; Decker, Stefan; Sahay, Ratnesh (ACM, 2015-09-16)
    Biosimulation models have been recently introduced to understand the exact causative factors that give rise to impairment in human organs. Finite Element Method (FEM) provides a mathematical framework to simulate dynamic ...
  • Extending inner-ear anatomical concepts in the Foundational Model of Anatomy (FMA) ontology 

    Khan, Yasar; Mehdi, Muntazir; Jha, Alokkumar; Raza, Saleem; Freitas, Andre; Jones, Marggie; Sahay, Ratnesh (IEEE, 2015-11-02)
    The inner ear is physically inaccessible in living humans, which leads to unique difficulties in studying its normal function and pathology as in other human organs. Recently, biosimulation model has gained a significant ...
  • Linked functional annotation for differentially expressed gene (DEG) demonstrated using Illumina Body Map 2.0 

    Jha, Alokkumar; Khan, Yasar; Iqbal, Aftab; Zappa, Achille; Mehdi, Muntazir; Sahay, Ratnesh; Rebholz-Schuhmann, Dietrich (CEUR-WS.org, 2015-12-09)
    Semantic Web technologies are core for the integration of disparate data resources. It can be used to exploit data from next generation sequencing (NGS) for therapeutic decisions regarding cancer. In this manuscript, ...
  • A linked data visualiser for finite element biosimulations 

    Mehdi, Muntazir; Khan, Yasar; Freitas, Andre; Jares, Joao; Raza, Saleem; Hasapis, Panagiotis; Sahay, Ratnesh (IEEE, 2016-02-04)
    Biosimulation models are used to understand the multiple or different causative factors that cause impairment in human organs. Finite Element Method (FEM) provide a mathematical framework to simulate dynamic biological ...
  • Privacy, security and policies: A review of problems and solutions with semantic web technologies 

    Kirrane, Sabrina; Villata, Serena; d’Aquin, Mathieu (IOS Press, 2018)
    Semantic Web technologies aim to simplify the distribution, sharing and exploitation of information and knowledge, across multiple distributed actors on the Web. As with all technologies that manipulate information, there ...
  • AFEL: Towards measuring online activities contributions to self-directed learning 

    d’Aquin, Mathieu; Adamou, Alessandro; Dietze, Stefan; Fetahu, Besnik; Gadiraju, Ujwal; Hasani-Mavriqi, Ilire; Holtz, Peter; Kimmerle, Joachim; Kowald, Dominik; Lex, Elisabeth; López Sola, Susana; Maturana, Ricardo A.; Sabol, Vedran; Troullinou, Pinelopi; Veas, Eduardo (CEUR-WS.org, 2017-09-12)
    More and more learning activities take place online in a selfdirected manner. Therefore, just as the idea of self-tracking activities for fitness purposes has gained momentum in the past few years, tools and methods for ...
  • Propagating data policies: a user study 

    Daga, Enrico; d’Aquin, Mathieu; Motta, Enrico (ACM, 2017-11-04)
    When publishing data, data licences are used to specify the actions that are permitted or prohibited, and the duties that target data consumers must comply with. However, in complex environments such as a smart city ...
  • An ontology-based approach to improve the accessibility of ROS-based robotic systems 

    Tiddi, Ilaria; Bastianelli, Emanuele; Bardaro, Gianluca; d’Aquin, Mathieu; Motta, Enrico (ACM, 2017-12-04)
    The focus of this work is to exploit ontologies to make robotic systems more accessible to non-expert users, therefore supporting the deployment of robot-integrated applications. Due to the increasing number of robotic ...
  • Demonstrating a linked data visualiser for finite element biosimulations 

    Mehdi, Muntazir; Khan, Yasar; Freitas, Andre; Jares, Joao; Raza, Saleem; Hasapis, Panagiotis; Sahay, Ratnesh (IEEE, 2016-02-04)
    Healthcare experts have recently turned towards the use of Biosimulation models to understand the multiple or different causative factors that cause impairment in human organs. The applications of biosimulations have been ...
  • A deep learning approach to genomics data for population scale clustering and ethnicity prediction 

    Karim, Md. Rezaul; Zappa, Achille; Sahay, Ratnesh; Rebholz-Schuhmann, Dietrich (CEUR-WS.org, 2017-05-28)
    The understanding of variations in genome sequences assists us in identifying people who are predisposed to common diseases, solving rare diseases, and finding corresponding population group of the individuals from a ...
  • Re-coding Black Mirror Chairs' Welcome & Organization 

    Troullinou, Pinelopi; d’Aquin, Mathieu; Tiddi, Ilaria (ACM, 2018-04-23)
    This volume of proceedings presents the papers from the 2nd edition of the interdisciplinary workshop Re-coding Black Mirror, held on April 24, 2018 in Lyon, France and co-located with The WEB Conference (WWW2018). ...
  • AFEL-Analytics for Everyday Learning 

    d’Aquin, Mathieu; Kowald, Dominik; Fessl, Angela; Lex, Elisabeth; Thalmann, Stefan (ACM, 2018-04-23)
    The goal of AFEL is to develop, pilot and evaluate methods and applications, which advance informal/collective learning as it surfaces implicitly in online social environments. The project is following a multi-disciplinary, ...
  • Facilitating scientometrics in learning analytics and educational data mining - The LAK dataset 

    Dietze, Stefan; Taibi, Davide; d’Aquin, Mathieu (IOS Press, 2016-11-06)
    The Learning Analytics and Knowledge (LAK) Dataset represents an unprecedented corpus which exposes a near complete collection of bibliographic resources for a specific research discipline, namely the connected areas of ...

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