Browsing Data Science Institute by Author "Heitmann, Benjamin"
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Architecture of Linked Data Applications
Heitmann, Benjamin; Cyganiak, Richard; Hayes, Conor; Decker, Stefan (CRC Press (Taylor & Francis), 2014)In this chapter, we first perform an empirical survey of RDF-based applications over most of the past decade, from 2003 to 2009. As the Linked Data principles where introduced in 2006, this allows us to describe the current ... -
Enabling case-based reasoning on the web of data
Heitmann, Benjamin; Hayes, Conor (2010-07-20)While Case-based reasoning (CBR) has successfully been deployed on the Web, its data models are typically inconsistent with existing information infrastructure and standards. In this paper, we examine how CBR can operate ... -
The interplay of theory and observation: a proposition for structured research on human behavior on the web
Heitmann, Benjamin (2009) -
Leveraging existing web frameworks for a SIOC explorer to browse online social communities
Heitmann, Benjamin; Oren, Eyal (2007)Since online SemanticWeb applications are based on existing Web infrastructure, developing these applications could leverage experiences with and infrastructure of existing frameworks. These frameworks need to be extended ... -
A Prototype to Explore Content and Context on Social Community Sites
Bojars, Uldis; Heitmann, Benjamin; Oren, Eyal (2007)The SIOC Ontology can be used to express information from the online community sites in a machine readable form using RDF. This rich data structure allows us to easily analyse and extract social relations from these ... -
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 ... -
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 ... -
Towards a reference architecture for Semantic Web applications
Heitmann, Benjamin; Hayes, Conor; Oren, Eyal (2009)The Semantic Web currently has two complementary architectural approaches: ¿Bottom-up¿ emergent best practices by the community and ¿top-down¿ prescriptive standards by standards bodies, leaving a gap regarding the concrete ... -
Using social media data for online television recommendation services at RTÉ Ireland
Barraza-Urbina, Andrea; Hromic, Hugo; Heitmann, Benjamin; Hayes, Conor; Hulpus, Ioana (2015-09)Raidió Teilifís Éireann (RTÉ) is the public service television and radio broadcaster in Ireland. Through on demand video services, RTÉ allows their users to catch up on television broadcasts via the RTÉ Player. The company ... -
Using social media for online television adaptation services at RTÉ Ireland
Barraza-Urbina, Andrea; Hromic, Hugo; Heitmann, Benjamin; Tamatam, Himasagar; Yañez, Andrea; Hayes, Conor (Insight Centre for Data Analytics, National University of Ireland, Galway, 2016)RTÉ (Raidió Teilifís Éireann) is the national provider of Television (TV) and radio in Ireland. RTÉ broadcasts its content online through the RTÉ Player and provides services to interact with its users using social media, ... -
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 ... -
XploDiv: Diversification Approach for Recommender Systems
Barraza-Urbina, Andrea; Heitmann, Benjamin; Hayes, Conor; Ramos, Angela Carrillo (INSIGHT Centre for Data Analytics, National University of Ireland, Galway, 2015)Recommender Systems 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 ...