Recent Submissions

  • Identifying equivalent relation paths in knowledge graphs 

    Mohamed, Sameh K.; Muñoz, Emir; Nováček, Vít; Vandenbussche, Pierre-Yves (Springer Verlag, 2017-06-19)
    Relation paths are sequences of relations with inverse that allow for complete exploration of knowledge graphs in a two-way unconstrained manner. They are powerful enough to encode complex relationships between entities ...
  • The role of negative results for choosing an evaluation approach - a recommender systems case study 

    Heitmann, Benjamin; Hayes, Conor (CEUR Workshop Proceedings, 2015-06-01)
    We describe a case study, which shows how important negative results are in uncovering biased evaluation methodologies. Our re- search question is how to compare a recommender algorithm that uses an RDF graph to a ...
  • XPLODIV: An exploitation-exploration aware diversification approach for Recommender Systems 

    Barraza-Urbina, Andrea; Heitmann, Benjamin; Hayes, Conor; Carrillo-Ramos, Angela (AAAI Press, 2015-07)
    Recommender Systems (RS) have emerged to guide users in the task of efficiently browsing/exploring a large product space, helping users to quickly identify interesting products. However, suggestions generated with traditional ...
  • Separating the wheat from the chaff: Evaluating success determinants for online Q&A communities 

    Aumayr, Erik; Hayes, Conor (NUI Galway, 2017-05-15)
    Researchers and community managers try to measure the success of online communities using a variety of success determinants, such as member activity, turnover and interaction. Although many success determinants have been ...
  • Soft cardinality constraints on XML data: How exceptions prove the business rule 

    Ferrarotti, Flavio; Hartmann, Sven; Link, Sebastian; Marin, Mauricio; Muñoz, Emir (Springer Verlag, 2013)
    We introduce soft cardinality constraints which need to be satisfied on average only, and thus permit violations in a controlled manner. Starting from a highly expressive but intractable class, we establish a fragment that ...
  • SPORTAL: Profiling the Content of Public SPARQL Endpoints 

    Hasnain, Ali; Mehmood, Qaiser; Sana e Zainab, Syeda; Hogan, Aidan (IGI Global, 2016)
    Access to hundreds of knowledge bases has been made available on the Web through public SPARQL endpoints. Unfortunately, few endpoints publish descriptions of their content (e.g., using VoID). It is thus unclear how agents ...
  • SPORTAL: Searching for Public SPARQL Endpoints 

    Hasnain, Ali; Mehmood, Qaiser; Zainab, Syeda Sana e; Hogan, Aidan (NUI Galway, 2016-10)
    There are hundreds of SPARQL endpoints on the Web, but finding an endpoint relevant to a client s needs is difficult: each endpoint acts like a black box, often without a description of its content. Herein we briefly ...
  • Lessons learnt from the Named Entity rEcognition and Linking (NEEL) challenge series 

    Rizzo, Giuseppe; Pereira, Bianca; Varga, Andrea; van Erp, Marieke; Cano Basave, Amparo Elizabeth (2017-03-13)
    The large number of tweets generated daily is providing policy makers with means to obtain insights into recent events around the globe in near real-time. The main barrier for extracting such insights is the impossibility ...
  • Semantic relation classification: task formalisation and refinement 

    Silva, Vivian S.; Hürliman, Manuela; Davis, Brian; Handschuh, Siegfried; Freitas, André (Association for Computational Linguistics, 2016-12-12)
    The identification of semantic relations between terms within texts is a fundamental task in Natural Language Processing which can support applications requiring a lightweight semantic interpretation model. Currently, ...
  • Dublin City University and Partners' participation in the INS and VTT Tracks at TRECVid 2016 

    Marsden, Mark; Mohedano, Eva; McGuinness, Kevin; Calafell, Andrea; Giro-i-Nieto, Xavier; O'Connor, Noel E.; Zhou, Jiang; Azavedo, Lucas; Daudert, Tobias; Davis, Brian; Hürlimann, Manuela; Afli, Haithem; Du, Jinhua; Ganguly, Debasis; Li, Wei; Way, Andy; Smeaton, Alan F. (2016-11-14)
    Dublin City University participated with a consortium of colleagues from NUI Galway and Universitat Polit`ecnica de Catalunya in two tasks in TRECVid 2016, Instance Search (INS) and Video to Text (VTT). For the INS task ...
  • A Twitter sentiment gold standard for the Brexit referendum 

    Hürlimann, Manuela; Davis, Brian; Cortis, Keith; Freitas, André; Handschuh, Siegfried; Fernández, Sergio (CEUR Workshop Proceedings, 2016-09-12)
    A Twitter Sentiment Gold Standard for the Brexit Referendum Manuela Hürlimann, Brian Davis Insight Centre for Data Analytics National University of Ireland Galway, Ireland {first.last}@insight-centre.org Keith Cortis, André ...
  • In or out? Real-time monitoring of BREXIT sentiment on Twitter 

    Vasiliu, Laurentiu; Freitas, André; Caroli, Frederico; McDermott, Ross; Zarrouk, Manel; Hürlimann, Manuela; Davis, Brian; Daudert, Tobias; Khaled, Malek Ben; Byrne, David; Fernández, Sergio; Cavallini, Angelo (CEUR Workshop Proceedings, 2016-09-12)
    The SSIX (Social Sentiment analysis financial IndeXes) project is a European Innovation Project sponsored by the European Commission under the Horizon 2020 framework. SSIX aims to provide European SMEs with a collection ...
  • Combining lexical and spatial knowledge to predict spatial relations between objects in images 

    Hürlimann, Manuela; Bos, Johan (ACL Anthology, 2016-08-11)
    Explicit representations of images are useful for linguistic applications related to images. We design a representation based on first-order models that capture the objects present in an image as well as their spatial ...
  • A hybrid method for rating prediction using linked data features and text reviews 

    Yumusak, Semih; Muñoz, Emir; Minervini, Pasquale; Dogdu, Erdogan; Kodaz, Halife (CEUR-WS.org, 2016)
    This paper describes our entry for the Linked Data Mining Challenge 2016, which poses the problem of classifying music albums as good or bad by mining Linked Data. The original labels are assigned according to aggregated ...
  • A linked data-based decision tree classifier to review movies 

    Aldarra, Suad; Muñoz, Emir (CEUR-WS.org, 2015)
    In this paper, we describe our contribution to the 2015 Linked Data Mining Challenge. The proposed task is concerned with the prediction of review of movies as good or bad , as does Metacritic website based on critics ...
  • Learning content patterns from linked data 

    Muñoz, Emir (CEUR-WS.org, 2014)
    Linked Data (LD) datasets (e.g., DBpedia, Freebase) are used in many knowledge extraction tasks due to the high variety of domains they cover. Unfortunately, many of these datasets do not provide a description for their ...
  • µRaptor: A DOM-based system with appetite for hCard elements 

    Muñoz, Emir; Costabello, Luca; Vandenbussche, Pierre-Yves (CEUR-WS.org, 2014)
    This paper describes µRaptor, a DOM-based method to extract hCard microformats from HTML pages stripped of microformat markup. µRaptor extracts DOM sub-trees, converts them into rules, and uses them to extract hCard ...
  • DRETa: extracting RDF from wikitables 

    Muñoz, Emir; Hogan, Aidan; Mileo, Alessandra (CEUR-WS.org, 2013)
    Tables are widely used in Wikipedia articles to display relational information - they are inherently concise and information rich. However, aside from info-boxe s, there are no automatic methods to exploit the integrated ...
  • Triplifying Wikipedia's tables 

    Muñoz, Emir; Hogan, Aidan; Mileo, Alessandra (CEUR-WS.org, 2013)
    We are currently investigating methods to triplify the content of Wikipedia's tables. We propose that existing knowledge-bases can be leveraged to semi-automatically extract high-quality facts (in the form of RDF triples) ...
  • The finite implication problem for expressive XML keys: Foundations, applications, and performance evaluation 

    Ferrarotti, Flavio; Hartmann, Sven; Link, Sebastian; Marin, Mauricio; Muñoz, Emir (Springer, 2013)
    The increasing popularity of XML for persistent data storage, processing and exchange has triggered the demand for efficient algorithms to manage XML data. Both industry and academia have long since recognized the importance ...

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