Personalised Diversification Using Intent-Aware Portfolio

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Title: Personalised Diversification Using Intent-Aware Portfolio
Authors: Wasilewski, Jacek
Hurley, Neil J.
Permanent link: http://hdl.handle.net/10197/9031
Date: 21-Jul-2017
Abstract: The intent-aware diversification framework considers a set of aspects associated with items to be recommended. A baseline recommendation is greedily re-ranked using an objective that promotes diversity across the aspects. In this paper the framework is analysed and a new intent-aware objective is derived that considers the minimum variance criterion, connecting the framework directly to portfolio diversification from finance. We derive an aspect model that supports the goal of minimum variance and that is faithful to the underlying baseline algorithm. We evaluate diversification capabilities of the proposed method on the MovieLens dataset.
Funding Details: Science Foundation Ireland
Type of material: Journal Article
Publisher: ACM
Copyright (published version): 2017 ACM
Keywords: Recommender Systems
DOI: 10.1145/3099023.3099067
Language: en
Status of Item: Peer reviewed
Is part of: Proceedings of the 25th Conference on User Modeling, Adaptation and Personalization
Conference Details: UMAP '17 Adjunct Publication of The 25th Conference on User Modeling, Adaptation and Personalization, Bratislava, Slovakia
Appears in Collections:Insight Research Collection

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