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The Curated Web: A Recommendation Challenge

Author(s)
Saaya, Zurina  
Rafter, Rachael  
Schaal, Markus  
Smyth, Barry  
Uri
http://hdl.handle.net/10197/9025
Date Issued
2013-10-16
Date Available
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
Sponsorship
Science Foundation Ireland
Type of Material
Conference Publication
Publisher
ACM
Copyright (Published Version)
2013 ACM
Subjects

Recommender Systems

DOI
10.1145/2507157.2507216
Language
English
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/
File(s)
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the curated web preprint.pdf

Size

800.04 KB

Format

Adobe PDF

Checksum (MD5)

5ca284c7110d3a72a8a6eb36c3268ad3

Owning collection
Insight Research Collection

Item descriptive metadata is released under a CC-0 (public domain) license: https://creativecommons.org/public-domain/cc0/.
All other content is subject to copyright.

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