Browsing by Author "LAWLESS, SEAMUS"
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CULTURA: Supporting Enhanced Exploration of Cultural Archives through Personalisation
LAWLESS, SEAMUS; HAMPSON, CORMAC; O'CONNOR, ALEXANDER; CONLAN, OWEN; WADE, VINCENT PATRICK (2012) -
Dual-Space Re-ranking Model for Document Retrieval
ZHOU, DONG; WADE, VINCENT PATRICK; LAWLESS, SEAMUS (2012-02-13)The field of information retrieval still strives to develop models which allow semantic information to be integrated in the ranking process to improve perform- ance in comparison to standard bag-of- words based models. A ... -
Dynamic Contextual eLearning - Dynamic Content Discovery, Capture and Learning Object Generation from Open Corpus Sources
LAWLESS, SEAMUS; LAWLESS, SEAMUS SEAN TOMAS (AACE - Association for the Advancement of Computing in Education, 2005) -
Dynamic Hypertext Generation for Reusing Open Corpus Content
LAWLESS, SEAMUS; STEICHEN, BEN; WADE, VINCENT PATRICK (ACM, 2009)Adaptive hypermedia systems traditionally focus on providing personalised learning services for formal or informal learners. The learning material is typically sourced from a proprietary set of closed corpus content. A ... -
Enhancing Access to Open Corpus Educational Content: Learning in the Wild
HEDERMAN, LUCY MARY; WADE, VINCENT PATRICK; LAWLESS, SEAMUS (2008)The World Wide Web (WWW) provides access to a vast array of interconnected educational content on almost every subject imaginable. A great deal of this content is ideal for incorporation into personalised eLearning ... -
Entity attribute ranking using learning to rank
LAWLESS, SEAMUS (2017) -
An Evaluation Framework for End-User Experience in Adaptive Systems
SHARP, MARY; WADE, VINCENT PATRICK; LAWLESS, SEAMUS; MULWA, CATHERINE (2011)The evaluation of adaptive and personalised systems is a difficult, complicated and very demanding endeavour due to the complex nature of these systems and the usability issues encountered. This demonstration introduces a ... -
An Evaluation Framework for End-User Experience in Adaptive Systems
SHARP, MARY; MULWA, CATHERINE; WADE, VINCENT PATRICK; LAWLESS, SEAMUS (LNCS, 2011)The evaluation of adaptive and personalised systems is a difficult, complicated and very demanding endeavour due to the complex nature of these systems and the usability issues encountered. This demonstration introduces a ... -
The Evaluation of Adaptive and User-Adaptive Systems: A Review
SHARP, MARY; WADE, VINCENT; LAWLESS, SEAMUS; MULWA, CATHERINE (2011)A current problem with the research of adaptive systems is the inconsistency of evaluation applied to the adaptive systems. However, evaluating an adaptive system is a difficult task due to the complexity of such systems. ... -
The Evaluation of Adaptive Technology-Enhanced Learning Systems
LAWLESS, SEAMUS; MULWA, CATHERINE; SHARP, MARY; WADE, VINCENT (2012-10)Adaptive technology enhanced learning has attracted significant interest with the promise of supporting individual learning tailored to the unique circumstances, preferences, and prior knowledge of a learner. Evaluation ... -
A Framework for the Evaluation of Adaptive IR Systems through Implicit Recommendation
O'DONNELL, EILEEN; LAWLESS, SEAMUS; GHORAB, MOHAMMED RAMI ELHUSSEIN; WADE, VINCENT; SHARP, MARY; MULWA, CATHERINE (Springer-Verlag LNCS, 2011)Personalised Information Retrieval (PIR) has gained considerable attention in recent literature. In PIR different stages of the retrieval process are adapted to the user, such as adapting the user?s query or the results. ... -
Improving Search via Personalized Query Expansion using Social Media
LAWLESS, SEAMUS; WADE, VINCENT PATRICK; ZHOU, DONG (Springer Verlag, 2012-06)Social tagging systems have gained increasing popularity as a method of annotating and categorizing a wide range of different web resources. Web search that utilizes social tagging data suffers from an extreme example of ... -
Inferring your expertise from Twitter: combining multiple types of user activity
XU, YU; LAWLESS, SEAMUS (ACM, 2017) -
A Late Fusion Approach to Cross-Lingual Document Re-ranking
ZHOU, DONG; WADE, VINCENT PATRICK; LAWLESS, SEAMUS (ACM, 2010)The field of information retrieval still strives to develop models which allow semantic information to be integrated in the ranking process to improve performance in comparison to standard bag- of-words based models. ... -
Leveraging Content from Open Corpus Sources for Technology Enhanced Learning
LAWLESS, SEAMUS (Trinity College Dublin, Trinity College Dublin, 2009)As educators attempt to incorporate the use of educational technologies in course curricula, the lack of appropriate and accessible digital content resources acts as a barrier to adoption. Quality educational digital ... -
Linked Open Corpus Models, Leveraging the Semantic Web for Adaptive Hypermedia
LAWLESS, SEAMUS; O'KEEFFE, IAN; WADE, VINCENT PATRICK; O'CONNOR, ALEXANDER (ACM, 2012)Despite the recent interest in extending Adaptive Hypermedia beyond the closed corpus domain and into the open corpus world of the web, many current approaches are limited by their reliance on closed metadata model ... -
Multilingual Adaptive Search for Digital Libraries
LAWLESS, SEAMUS; GHORAB, MOHAMMED RAMI ELHUSSEIN; O'CONNOR, ALEXANDER; ZHOU, DONG; WADE, VINCENT (LNCS, 2011)We describe a framework for Adaptive Multilingual Information Retrieval (AMIR) which allows multilingual resource discovery and delivery using on-the-fly machine translation of documents and queries. Result documents are ... -
Multilingual User Modeling for Personalized Re-ranking of Multilingual Web Search Results
GHORAB, MOHAMMED RAMI; ZHOU, DONG; LAWLESS, SEAMUS; WADE, VINCENT PATRICK (2012-07-16)This paper proposes a novel method to represent user models in a multilingual manner which caters for multilingual Web search users. Furthermore, an evaluation is presented which examines a result re-ranking algorithm that ... -
OCCS: Enabling the Dynamic Discovery, Harvesting and Delivery of Educational Content from Open Corpus Sources
WADE, VINCENT PATRICK; LAWLESS, SEAMUS; LAWLESS, SEAMUS SEAN TOMAS; HEDERMAN, LUCY MARY (2008)The World Wide Web (WWW) provides access to a vast array of educational content, a great deal of which is ideal for incorporation into eLearning experiences. However sourcing, harvesting and incorporating appropriate ...