Abstract
We present a simulation framework to examine the impact of sensor noise on the performance of user models in the museum domain. Our contributions are: (1) models to simulate noisy visit trajectories as time-stamped sequences of (x, y) positional coordinates which reflect walking and hovering behaviour; (2) a discriminative inference model that distinguishes between hovering and walking on the basis of (simulated) noisy sensor observations; (3) a model that infers viewed exhibits from hovering coordinates; and (4) a model that predicts the next exhibit on the basis of inferred (rather than known) viewed exhibits. Our staged evaluation assesses the effect of these models (in combination with sensor noise) on inferential and predictive performance, thus shedding light on the reliability attributed to inferences drawn from sensor observations.
| Original language | English |
|---|---|
| Title of host publication | Proceedings of the 9th Workshop on Intelligent Techniques for Web Personalization & Recommender Systems |
| Editors | Sarabjot Singh Anand, Dietmar Jannach, Bamshad Mobasher, Alfred Kobsa |
| Place of Publication | Aachen Germany |
| Publisher | CEUR-WS |
| Pages | 49 - 56 |
| Number of pages | 8 |
| Volume | 756 |
| Publication status | Published - 2011 |
| Event | International Workshop on Intelligent Techniques for Web Personalization and Recommender Systems (ITWP) 2011 - Barcelona, Spain Duration: 16 Jul 2011 → 16 Jul 2011 Conference number: 9th |
Workshop
| Workshop | International Workshop on Intelligent Techniques for Web Personalization and Recommender Systems (ITWP) 2011 |
|---|---|
| Abbreviated title | ITWP 2011 |
| Country | Spain |
| City | Barcelona |
| Period | 16/07/11 → 16/07/11 |
Cite this
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Modelling and predicting movements of museum visitors : A simulation framework for assessing the impact of sensor noise on model performance. / Bohnert, Fabian; Zukerman, Ingrid; Albrecht, David William; Baldwin, Timothy.
Proceedings of the 9th Workshop on Intelligent Techniques for Web Personalization & Recommender Systems. ed. / Sarabjot Singh Anand; Dietmar Jannach; Bamshad Mobasher; Alfred Kobsa. Vol. 756 Aachen Germany : CEUR-WS, 2011. p. 49 - 56.Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research › peer-review
TY - GEN
T1 - Modelling and predicting movements of museum visitors
T2 - A simulation framework for assessing the impact of sensor noise on model performance
AU - Bohnert, Fabian
AU - Zukerman, Ingrid
AU - Albrecht, David William
AU - Baldwin, Timothy
PY - 2011
Y1 - 2011
N2 - We present a simulation framework to examine the impact of sensor noise on the performance of user models in the museum domain. Our contributions are: (1) models to simulate noisy visit trajectories as time-stamped sequences of (x, y) positional coordinates which reflect walking and hovering behaviour; (2) a discriminative inference model that distinguishes between hovering and walking on the basis of (simulated) noisy sensor observations; (3) a model that infers viewed exhibits from hovering coordinates; and (4) a model that predicts the next exhibit on the basis of inferred (rather than known) viewed exhibits. Our staged evaluation assesses the effect of these models (in combination with sensor noise) on inferential and predictive performance, thus shedding light on the reliability attributed to inferences drawn from sensor observations.
AB - We present a simulation framework to examine the impact of sensor noise on the performance of user models in the museum domain. Our contributions are: (1) models to simulate noisy visit trajectories as time-stamped sequences of (x, y) positional coordinates which reflect walking and hovering behaviour; (2) a discriminative inference model that distinguishes between hovering and walking on the basis of (simulated) noisy sensor observations; (3) a model that infers viewed exhibits from hovering coordinates; and (4) a model that predicts the next exhibit on the basis of inferred (rather than known) viewed exhibits. Our staged evaluation assesses the effect of these models (in combination with sensor noise) on inferential and predictive performance, thus shedding light on the reliability attributed to inferences drawn from sensor observations.
UR - http://www.scopus.com/inward/record.url?scp=84891930122&partnerID=8YFLogxK
M3 - Conference Paper
VL - 756
SP - 49
EP - 56
BT - Proceedings of the 9th Workshop on Intelligent Techniques for Web Personalization & Recommender Systems
A2 - Anand, Sarabjot Singh
A2 - Jannach, Dietmar
A2 - Mobasher, Bamshad
A2 - Kobsa, Alfred
PB - CEUR-WS
CY - Aachen Germany
ER -