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    Author
    Hayes, Conor (11)
    Aumayr, Erik (4)Hulpus, Ioana (4)Greene, Derek (2)Heitmann, Benjamin (2)... View MoreSubjectData analytics (2)Online communities (2)User behaviour (2)Artificial Intelligence (1)Cognitive science (1)... View MoreDate Issued2017 (2)2016 (2)2015 (3)2014 (2)2013 (2)TypeConference Paper (11)

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    Modelling User Behaviour in Online Q&A Communities for Customer Support 

    Aumayr, Erik; Hayes, Conor (Springer, 2014)
    [no abstract available]
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    On the correlation between topic and user behaviour in online communities 

    Aumayr, Erik; Hayes, Conor (ICWSM-16, 2016-05-20)
    In the advancement of a better understanding of user behaviour on the Internet, clustering approaches are used as a means to group and categorise online communities. Although clustering approaches indicate similarity between ...
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    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 ...
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    Path-based semantic relatedness on linked data and its use to word and entity disambiguation 

    Hulpus, Ioana; Prangnawarat, Narumol; Hayes, Conor (2015)
    Semantic relatedness and disambiguation are fundamental problems for linking text documents to the Web of Data. There are many approaches dealing with both problems but most of them rely on word or concept distribution ...
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    SemStim at the Linked Open Data-enabled Recommender Systems 2014 challenge 

    Heitmann, Benjamin; Hayes, Conor (Springer, 2014-10-14)
    SemStim is a graph-based recommendation algorithm which is based on Spreading Activation and adds targeted activation and duration constraints. SemStim is not affected by data sparsity, the cold-start problem or data quality ...
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    Unsupervised Graph-Based Topic Labelling using DBpedia 

    Hulpus, Ioana; Hayes, Conor; Karnstedt, Marcel; Greene, Derek (2013)
    Automated topic labelling brings benefits for users aiming at analysing and understanding document collections, as well as for search engines targetting at the linkage between groups of words and their inherent topics. ...
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    Kanopy: Analysing the Semantic Network around Document Topics 

    Hulpus, Ioana; Hayes, Conor; Karnstedt, Marcel; Greene, Derek; Jozwowicz, Marek (Springer, 2013)
    External knowledge bases, both generic and domain specific, available on the Web of Data have the potential of enriching the content of text documents with structured information. We present the Kanopy system that makes ...
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    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 ...
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    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 ...
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    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 ...
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