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A personalized and context-aware news offer for mobile devices

Toon De Pessemier UGent, Kris Vanhecke UGent and Luc Martens UGent (2016) Lecture Notes in Business Information Processing. In Lecture Notes in Business Information Processing 246. p.147-168
abstract
For classical domains, such as movies, recommender systems have proven their usefulness. But recommending news is more challenging due to the short life span of news content and the demand for up-to-date recommendations. This paper presents a news recommendation service with a content-based algorithm that uses features of a search engine for content processing and indexing, and a collaborative filtering algorithm for serendipity. The extension towards a context-aware algorithm is made to assess the information value of context in a mobile environment through a user study. Analyzing interaction behavior and feedback of users on three recommendation approaches shows that interaction with the content is crucial input for user modeling. Context-aware recommendations using time and device type as context data outperform traditional recommendations with an accuracy gain dependent on the contextual situation. These findings demonstrate that the user experience of news services can be improved by a personalized context-aware news offer.
Please use this url to cite or link to this publication:
author
organization
year
type
conference (proceedingsPaper)
publication status
published
subject
keyword
Real-time, Context-aware, Mobile, News, User evaluation, RECOMMENDATIONS, SYSTEMS, Recommender system
in
Lecture Notes in Business Information Processing
editor
Valérie Monfort, Karl-Heinz Krempels, Tim A. Majchrzak and Ziga Turk
series title
Lecture Notes in Business Information Processing
volume
246
issue title
WEB INFORMATION SYSTEMS AND TECHNOLOGIES, WEBIST 2015
pages
147 - 168
publisher
Springer International Publishing Switzerland
place of publication
Switzerland
conference name
11th International Conference on Web Information Systems and Technologies (WEBIST 2015)
conference location
Lisbon, PORTUGAL
conference start
2015-05-20
conference end
2015-05-22
Web of Science type
Proceedings Paper
Web of Science id
000376161300008
ISSN
1865-1348
ISBN
978-3-319-30996-5
DOI
10.1007/978-3-319-30996-5_8
language
English
UGent publication?
yes
classification
P1
copyright statement
I have transferred the copyright for this publication to the publisher
id
8196939
handle
http://hdl.handle.net/1854/LU-8196939
date created
2016-11-29 09:51:02
date last changed
2017-01-02 09:53:05
@inproceedings{8196939,
  abstract     = {For classical domains, such as movies, recommender systems have proven their usefulness. But recommending news is more challenging due to the short life span of news content and the demand for up-to-date recommendations. This paper presents a news recommendation service with a content-based algorithm that uses features of a search engine for content processing and indexing, and a collaborative filtering algorithm for serendipity. The extension towards a context-aware algorithm is made to assess the information value of context in a mobile environment through a user study. Analyzing interaction behavior and feedback of users on three recommendation approaches shows that interaction with the content is crucial input for user modeling. Context-aware recommendations using time and device type as context data outperform traditional recommendations with an accuracy gain dependent on the contextual situation. These findings demonstrate that the user experience of news services can be improved by a personalized context-aware news offer.},
  author       = {De Pessemier, Toon and Vanhecke, Kris and Martens, Luc},
  booktitle    = {Lecture Notes in Business Information Processing},
  editor       = {Monfort, Val{\'e}rie and Krempels, Karl-Heinz and Majchrzak, Tim A. and Turk, Ziga},
  isbn         = {978-3-319-30996-5},
  issn         = {1865-1348},
  keyword      = {Real-time,Context-aware,Mobile,News,User evaluation,RECOMMENDATIONS,SYSTEMS,Recommender system},
  language     = {eng},
  location     = {Lisbon, PORTUGAL},
  pages        = {147--168},
  publisher    = {Springer International Publishing Switzerland},
  title        = {A personalized and context-aware news offer for mobile devices},
  url          = {http://dx.doi.org/10.1007/978-3-319-30996-5\_8},
  volume       = {246},
  year         = {2016},
}

Chicago
De Pessemier, Toon, Kris Vanhecke, and Luc Martens. 2016. “A Personalized and Context-aware News Offer for Mobile Devices.” In Lecture Notes in Business Information Processing, ed. Valérie Monfort, Karl-Heinz Krempels, Tim A. Majchrzak, and Ziga Turk, 246:147–168. Switzerland: Springer International Publishing Switzerland.
APA
De Pessemier, T., Vanhecke, K., & Martens, L. (2016). A personalized and context-aware news offer for mobile devices. In V. Monfort, K.-H. Krempels, T. A. Majchrzak, & Z. Turk (Eds.), Lecture Notes in Business Information Processing (Vol. 246, pp. 147–168). Presented at the 11th International Conference on Web Information Systems and Technologies (WEBIST 2015), Switzerland: Springer International Publishing Switzerland.
Vancouver
1.
De Pessemier T, Vanhecke K, Martens L. A personalized and context-aware news offer for mobile devices. In: Monfort V, Krempels K-H, Majchrzak TA, Turk Z, editors. Lecture Notes in Business Information Processing. Switzerland: Springer International Publishing Switzerland; 2016. p. 147–68.
MLA
De Pessemier, Toon, Kris Vanhecke, and Luc Martens. “A Personalized and Context-aware News Offer for Mobile Devices.” Lecture Notes in Business Information Processing. Ed. Valérie Monfort et al. Vol. 246. Switzerland: Springer International Publishing Switzerland, 2016. 147–168. Print.