The Curated Web: A Recommendation Challenge
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|Title:||The Curated Web: A Recommendation Challenge||Authors:||Saaya, Zurina
|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|
|Appears in Collections:||Insight Research Collection|
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