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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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A Live-User Study of Opinionated Explanations for Recommender Systems
TLDR
This paper describes an approach for generating rich and compelling explanations in recommender systems, based on opinions mined from user-generated reviews. Expand
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The Condemnation of Blackness: Race, Crime, and the Making of Modern Urban America
* List of Illustrations * Introduction: The Mismeasure of Crime * Saving the Nation: The Racial Data Revolution and the Negro Problem * Writing Crime into Race: Racial Criminalization in the Age ofExpand
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Where Did All the White Criminals Go?: Reconfiguring Race and Crime on the Road to Mass Incarceration
This article highlights racialized constructions of criminality that surfaced in the wake of mass migrations and immigrations of African American and European workers to the industrial North duringExpand
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Opinionated Explanations for Recommendation Systems
TLDR
This paper describes a novel approach for generating explanations for recommender systems based on opinions in user-generated reviews. Expand
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On the Use of Opinionated Explanations to Rank and Justify Recommendations
TLDR
We use the strength of an explanation as the primary ranking signal for ordering recommendations, instead of more conventional ranking measures such as relevance or similarity. Expand
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Generating Personalised and Opinionated Review Summaries
TLDR
This paper presents a method for constructing personalised summaries of items based on opinions from textual reviews. Expand
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On the Pros and Cons of Explanation-Based Ranking
TLDR
We extend recent work on the use of explanations by recommender systems. Expand
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Explanation-based Ranking in Opinionated Recommender Systems
The 24th Irish Conference on Artificial Intelligence and Cognitive Science, University College Dublin, Ireland, 20-21 September 2016
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Great Explanations : Opinionated Explanations for Recommendation
Explaining recommendations helps users to make better, more satisfying decisions. We describe a novel approach to explanation for recommender systems, one that drives the recommendation process,Expand
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