The Curated Web: A Recommendation Challenge

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Title: The Curated Web: A Recommendation Challenge
Authors: Saaya, ZurinaRafter, RachaelSchaal, MarkusSmyth, Barry
Permanent link: http://hdl.handle.net/10197/9025
Date: 16-Oct-2013
Online since: 2017-11-01T16:32:17Z
Abstract: In this paper we consider the application of content-based recommendation techniques to web curation services which allow users to curate and share topical collections of content (e.g. images, news, web pages etc.). Curation services like Pinterest are now a mainstay of the modern web and present a range of interesting recommendation challenges. In this paper we consider the task of recommending collections to users and evaluate a range of different content-based techniques across a variety of content signals. We present the results of a large-scale evaluation using data from the Scoop.it web page curation service
Funding Details: Science Foundation Ireland
Type of material: Conference Publication
Publisher: ACM
Copyright (published version): 2013 ACM
Keywords: Recommender Systems
DOI: 10.1145/2507157.2507216
Language: en
Status of Item: Peer reviewed
Conference Details: RecSys’13, Hong Kong, China
This item is made available under a Creative Commons License: https://creativecommons.org/licenses/by-nc-nd/3.0/ie/
Appears in Collections:Insight Research Collection

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