• Publications
  • Influence
Case-Based User Profiling for Content Personalisation
TLDR
We describe and evaluate a two-stage personalised information retrieval system that combines a server-side similarity-based retrieval component with a client-side case-based personalisation component. Expand
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Personalised Retrieval for Online Recruitment Services
The BCS/ IRSG 22nd Annual Colloquium on Information Retrieval (IRSG 2000), Cambridge, UK, 5-7 April, 2000
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Passive Profiling from Server Logs in an Online Recruitment Environment
TLDR
We address the issues involved in automatically learning user profiles and focus on a key assumption that has been adopted by some systems: that accurate user profiles can be generated directly from analysing certain behaviours such as the clickstream and read-time data. Expand
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Great Explanations: Opinionated Explanations for Recommendations
TLDR
A novel approach to explanation for recommender systems, one that drives the recommendation ranking process, while at the same time providing the user with useful insights into the reason why items have been recommended and the trade-offs they may need to consider when making their choice. Expand
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An Analysis of Recommender Algorithms for Online News
TLDR
This paper presents the recommendation algorithms used by the Insight UCD team participating in the CLEF-NewsREEL 2014 online news recommendation challenge. Expand
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Personalized activity based eLearning
TLDR
The aim of personalizing web information systems is to tailor content (media) to the user's personal preferences, goals and context, in turn increasing the reusability of that content. Expand
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Conversational Collaborative Recommendation – An Experimental Analysis
TLDR
We investigate the usefulness of conversational feedback in collaborative recommendation and provide experimental evidence to support this claim. Expand
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The Recommendation Game: Using a Game-with-a-Purpose to Generate Recommendation Data
TLDR
We propose a casual Facebook game to capture recommendation data as a side-effect of gameplay. Expand
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News Recommenders: Real-Time, Real-Life Experiences
TLDR
In this paper we share our experiences of working with a real-time news recommendation framework with real-world user and data. Expand
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The curated web: a recommendation challenge
TLDR
We evaluate the efficacy of different types of content signals during user profiling and collection indexing, from high-level collection descriptions to detailed information about the contents of individual pages. Expand
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