The Curated Web: A Recommendation Challenge
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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 | 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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