Abstract
| Original language | English |
|---|---|
| Title of host publication | Changing Television Environments |
| Subtitle of host publication | 6th European Conference, EUROITV 2008, Proceedings |
| Editors | Manfred Tscheligi, Marianna Obrist, Artur Lugmayr |
| Publisher | Springer |
| Pages | 82-91 |
| ISBN (Electronic) | 978-3-540-69478-6 |
| ISBN (Print) | 978-3-540-69477-9 |
| DOIs | |
| Publication status | Published - 2008 |
| MoE publication type | A4 Article in a conference publication |
| Event | 6th European Conference, EUROITV 2008 - Salzburg, Austria Duration: 3 Jul 2008 → 4 Jul 2008 |
Publication series
| Series | Lecture Notes in Computer Science |
|---|---|
| Volume | 5066 |
| ISSN | 0302-9743 |
Conference
| Conference | 6th European Conference, EUROITV 2008 |
|---|---|
| Abbreviated title | EUROITV 2008 |
| Country | Austria |
| City | Salzburg |
| Period | 3/07/08 → 4/07/08 |
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Keywords
- smart home
- TV recommender system
- user modelling
- intelligent user service
- user needs
Cite this
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Unobtrusive Dynamic Modelling of TV Program Preferences in a Household. / Vildjiounaite, Elena; Kyllönen, Vesa; Hannula, Tero; Alahuhta, Petteri.
Changing Television Environments: 6th European Conference, EUROITV 2008, Proceedings. ed. / Manfred Tscheligi; Marianna Obrist; Artur Lugmayr. Springer, 2008. p. 82-91 (Lecture Notes in Computer Science, Vol. 5066).Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceedings › Scientific › peer-review
TY - GEN
T1 - Unobtrusive Dynamic Modelling of TV Program Preferences in a Household
AU - Vildjiounaite, Elena
AU - Kyllönen, Vesa
AU - Hannula, Tero
AU - Alahuhta, Petteri
PY - 2008
Y1 - 2008
N2 - Majority of recommender systems require explicit user interaction (ranking of movies and TV programs and/or their metadata, such as genres, actors etc), which requires user time and effort. Furthermore, often such ranking is done separately by each person, while merging these manually acquired preferences in multi-user environments remains largely unsolved problem. This work presents a method to learn a model of multi-user environment in intelligent home from implicit interactions: the choices which family members make together and separately. In tests on TV viewing histories of twenty families, acquired during two months, the method has achieved prediction accuracy comparable with the accuracy of systems which require explicit user ratings: a set of TV programs, actually viewed during each test session (average set size was 2.2 programs per viewing session), was recommended among five top choices in 60% of cases on average, despite training on small data sets.
AB - Majority of recommender systems require explicit user interaction (ranking of movies and TV programs and/or their metadata, such as genres, actors etc), which requires user time and effort. Furthermore, often such ranking is done separately by each person, while merging these manually acquired preferences in multi-user environments remains largely unsolved problem. This work presents a method to learn a model of multi-user environment in intelligent home from implicit interactions: the choices which family members make together and separately. In tests on TV viewing histories of twenty families, acquired during two months, the method has achieved prediction accuracy comparable with the accuracy of systems which require explicit user ratings: a set of TV programs, actually viewed during each test session (average set size was 2.2 programs per viewing session), was recommended among five top choices in 60% of cases on average, despite training on small data sets.
KW - smart home
KW - TV recommender system
KW - user modelling
KW - intelligent user service
KW - user needs
U2 - 10.1007/978-3-540-69478-6_9
DO - 10.1007/978-3-540-69478-6_9
M3 - Conference article in proceedings
SN - 978-3-540-69477-9
T3 - Lecture Notes in Computer Science
SP - 82
EP - 91
BT - Changing Television Environments
A2 - Tscheligi, Manfred
A2 - Obrist, Marianna
A2 - Lugmayr, Artur
PB - Springer
ER -