Now showing items 22-41 of 153

  • DAW: Duplicate-AWare Federated Query Processing over the Web of Data 

    Parreira, Josiane Xavier; Deus, Helena F.; Hauswirth, Manfred (Springer, 2013)
    Over the last years the Web of Data has developed into a large compendium of interlinked data sets from multiple domains. Due to the decentralised architecture of this compendium, several of these datasets contain duplicated ...
  • Deep convolution neural network model to predict relapse in breast cancer 

    Jha, Alokkumar; Verma, Ghanshyam; Khan, Yasar; Mehmood, Qaiser; Rebholz-Schuhmann, Dietrich; Sahay, Ratnesh (IEEE, 2018-12-17)
    A mishap in anti-cancer drug distribution is critical in breast cancer patients due to poor prediction model to identify the treatment regime in ER+ve and ER-ve (Estrogen Receptor (ER)) patients. The traditional method for ...
  • 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 ...
  • 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, ...
  • 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 ...
  • 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 ...
  • Discovering Domain-Specific Public SPARQL Endpoints: A Life-Sciences Use-Case 

    Iqbal, Aftab (2014)
    A significant portion of the LOD cloud consists of Life Sciences data sets. The LOD cloud contains billions of clinical facts linked together forming an interlinked Web of Clinical Data . However, tools for new publishers ...
  • Domain-independent term extraction through domain modelling 

    Bordea, Georgeta; Buitelaar, Paul; Polajnar, Tamara (10th International Conference on Terminology and Artificial Intelligence, 2013-09-11)
    Extracting general or intermediate level terms is a relevant problem that has not received much attention in literature. Current approaches for term extraction rely on contrastive corpora to identify domain-specific terms, ...
  • Engineering an aligned gold-standard corpus of human to machine oriented Controlled Natural Language 

    Hazem Safwat; Brian Davis; Manel Zarrouk (IEEE, 2018-12-03)
    Knowledge base creation and population are an essential formal backbone for a variety of intelligent applications, decision support and expert systems and intelligent search. While the abundance of unstructured text helps ...
  • Enhancing statistical machine translation with bilingual terminology in a CAT environment 

    Arcan, Mihael; Turchi, Marco; Tonelli, Sara; Buitelaar, Paul (Association for Machine Translation in the Americas, 2014-10-22)
    In this paper, we address the problem of extracting and integrating bilingual terminology into a Statistical Machine Translation (SMT) system for a Computer Aided Translation (CAT) tool scenario. We develop a framework ...
  • Entity Linking with Multiple Knowledge Bases: An Ontology Modularization Approach 

    Pereira, Bianca (Springer, 2014-10-19)
    The recognition of entities in text is the basis for a series of applications. Synonymy and Ambiguity are among the biggest challenges in identifying such entities. Both challenges are addressed by Entity Linking, the task ...
  • The ESSOT system goes wild: an easy way for translating ontologies 

    Arcan, Mihael; Dragoni, Mauro; Buitelaar, Paul (CEUR-WS.org, 2016-10-17)
    To enable knowledge access across languages, ontologies that are often represented only in English, need to be translated into different languages. This activity is time consuming, therefore, smart solutions are required ...
  • ESSOT: an expert supporting system for ontology translation 

    Arcan, Mihael; Dragoni, Mauro; Buitelaar, Paul (Springer Verlag, 2016)
    To enable knowledge access across languages, ontologies, mostly represented only in English, need to be translated into different languages. The main challenge in translating ontologies with machine translation is to ...
  • Event Analysis in Social Media Using Clustering of Heterogeneous Information Networks 

    Prangnawarat, Narumol; Hulpus, Ioana; Hayes, Conor (The 28th International FLAIRS Conference (AAAI Publications) (AAAI), 2015)
    In this paper, we propose a novel approach for social media event finding in order to support fast access to information that users find relevant. While there are many approaches related to this problem, they mainly focus ...
  • Expanding wordnets to new languages with multilingual sense disambiguation 

    Arcan, Mihael; McCrae, John P.; Buitelaar, Paul (The COLING 2016 Organizing Committee, 2016-12-11)
    Princeton WordNet is one of the most important resources for natural language processing, but is only available for English. While it has been translated using the expand approach to many other languages, this is an ...
  • Experiments with term translation 

    Arcan, Mihael; Federmann, Christian; Buitelaar, Paul (Association for Computational Linguistics, 2012-12-08)
    In this article we investigate the translation of financial terms from English into German in the isolation of an ontology vocabulary. For this study we automatically built new domain-specific resources from the translation ...
  • 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 ...
  • Extending largeRDFBench for multi-source data at scale for SPARQL endpoint federation 

    Hasnain, Ali; Saleem, Muhammad; Ngomo, Axel-Cyrille Ngonga; Rebholz-Schuhmann, Dietrich (IOS Press, 2018)
    Querying the Web of Data is highly motivated by the use of federation approaches mainly SPARQL query federation when the data is available through endpoints. Different benchmarks have been proposed to exploit the full ...
  • Financial Industry Ontologies for Risk and Regulation Data (FIORD): a position paper 

    Koumpis, Adamantios (2013)
    This paper presents a proposed approach to address risk andregulation management within the highly active and volatile financial domainby employing semantic based technologies within a collaborative networksenvironment. ...
  • FinSentiA: sentiment analysis in English financial microblogs 

    Gaillat, Thomas; Sousa, Annanda; Zarrouk, Manel; Davis, Brian (NUI Galway, 2018-05-14)
    The objective of this paper is to report on the building of a Sentiment Analysis (SA) system dedicated to financial microblogs in English. The purpose of our work is to build a financial classifier that predicts the sentiment ...