Zobrazeno 1 - 10
of 16
pro vyhledávání: '"Rachael Rafter"'
Autor:
Vincent Wade, Rachael Rafter, Eddie Walsh, Ian O'Keeffe, Bilal Yousuf, Owen Conlan, Athanasios Staikopoulos
Publikováno v:
Computer Science and Information Systems. 11:343-367
Personalised web information systems have in recent years been evolving to provide richer and more tailored experiences for users than ever before. In order to provide even more interactive experiences as well as to address new opportunities, the nex
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ad7734bfae0686c1252e2ad4ca7dbf48
https://doi.org/10.2298/csis121227012s
https://doi.org/10.2298/csis121227012s
Publikováno v:
UMAP
Recommender systems have become a familiar part of our online experiences, suggesting movies to watch, music to listen to, and books to read, among other things. To make relevant suggestions, recommender systems need an accurate picture of our prefer
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::58011fdebf2b7f5b950dc1da06cbde47
https://doi.org/10.1145/2930238.2930260
https://doi.org/10.1145/2930238.2930260
Publikováno v:
RecSys
This paper describes a casual Facebook game to capture recommendation data as a side-effect of gameplay. We show how this data can be used to make successful recommendations as part of a live-user trial.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1623b178145b7361555610dd9a16e6cf
https://doi.org/10.1145/2792838.2799675
https://doi.org/10.1145/2792838.2799675
Publikováno v:
Research and Development in Intelligent Systems XXXII ISBN: 9783319250304
SGAI Conf.
SGAI Conf.
This paper describes a novel approach for generating explanations for recommender systems based on opinions in user-generated reviews. We show how these opinions can be used to construct helpful and compelling explanations at recommendation time. The
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e50c70363c3d334d183511f70600f34e
https://doi.org/10.1007/978-3-319-25032-8_25
https://doi.org/10.1007/978-3-319-25032-8_25
Publikováno v:
Case-Based Reasoning Research and Development ISBN: 9783319245850
ICCBR
ICCBR
Explaining recommendations helps users to make better decisions. We describe a novel approach to explanation for recommender systems, one that drives the recommendation ranking process, while at the same time providing the user with useful insights i
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::479db3b812ff199e8aa5d25e077404e9
https://doi.org/10.1007/978-3-319-24586-7_17
https://doi.org/10.1007/978-3-319-24586-7_17
Publikováno v:
Proceedings of the AAAI Conference on Human Computation and Crowdsourcing. 3:38-39
Recommender systems learn about our preferences to make targeted suggestions. In this paper we outline a novel game-with-a-purpose designed to infer preferences at scale as a side-effect of gameplay. We evaluate the utility of this data in a recommen
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3da02f1fd3b6fdbb7cd43591e1cb458f
https://doi.org/10.1609/hcomp.v3i1.13241
https://doi.org/10.1609/hcomp.v3i1.13241
Publikováno v:
RecSys
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 a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::81c86ddaf7688aac6eba71f6f70f7e53
https://doi.org/10.1145/2507157.2507216
https://doi.org/10.1145/2507157.2507216
Publikováno v:
IUI Companion
Information streams allow social network users to receive and interact with the latest messages from friends and followers. But as our social graphs grow and mature it becomes increasingly difficult to deal with the information overload that these re
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4dee6e5309e07afde33c9f3b3475dab8
https://doi.org/10.1145/2451176.2451219
https://doi.org/10.1145/2451176.2451219
Publikováno v:
User Modeling, Adaptation, and Personalization ISBN: 9783642388439
UMAP
UMAP
A new generation of curation services provides users with a set of tools to manually curate and manage topical collections of content. However, given curation is ultimately a manual effort, it still requires significant effort on the part of the cura
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::42953fc78396586b97cf53f0a6804952
https://doi.org/10.1007/978-3-642-38844-6_20
https://doi.org/10.1007/978-3-642-38844-6_20
Publikováno v:
Research and Development in Intelligent Systems XXIX ISBN: 9781447147381
SGAI Conf.
SGAI Conf.
In the past recommender systems have relied heavily on the availability of ratings data as the raw material for recommendation. Moreover, popular collaborative filtering approaches generate recommendations by drawing on the interests of users who sha
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9bef20bdbd1bf6c518144313baff2867
https://doi.org/10.1007/978-1-4471-4739-8_24
https://doi.org/10.1007/978-1-4471-4739-8_24