The Curated Web: A Recommendation Challenge

Files in This Item:
File Description SizeFormat 
the curated web preprint.pdf800.04 kBAdobe PDFDownload
Title: The Curated Web: A Recommendation Challenge
Authors: Saaya, Zurina
Rafter, Rachael
Schaal, Markus
Smyth, Barry
Permanent link: http://hdl.handle.net/10197/9025
Date: 16-Oct-2013
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
Appears in Collections:Insight Research Collection

Show full item record

SCOPUSTM   
Citations 50

1
Last Week
0
Last month
checked on Jun 23, 2018

Download(s)

10
checked on May 25, 2018

Google ScholarTM

Check

Altmetric


This item is available under the Attribution-NonCommercial-NoDerivs 3.0 Ireland. No item may be reproduced for commercial purposes. For other possible restrictions on use please refer to the publisher's URL where this is made available, or to notes contained in the item itself. Other terms may apply.