Advanced search
2 files | 5.90 MB

A personalized and context-aware news offer for mobile devices

Toon De Pessemier (UGent), Kris Vanhecke (UGent) and Luc Martens (UGent)
Author
Organization
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.
Keywords
Real-time, Context-aware, Mobile, News, User evaluation, RECOMMENDATIONS, SYSTEMS, Recommender system

Downloads

  • WICA 687a.pdf
    • full text
    • |
    • open access
    • |
    • PDF
    • |
    • 2.84 MB
    • full text
    • |
    • UGent only
    • |
    • PDF
    • |
    • 3.06 MB

Citation

Please use this url to cite or link to this publication:

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.
@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},
}

Altmetric
View in Altmetric
Web of Science
Times cited: