@inproceedings{9946a8d6d15f49e3bd05fba0dabf2871,
title = "Using collaborative models to adaptively predict visitor locations in museums",
abstract = "The vast amounts of information presented in museums can be overwhelming to a visitor, whose receptivity and time are typically limited. Hence, s/he might have difficulties selecting interesting exhibits to view within the available time. Mobile, context-aware guides offer the opportunity to improve a visitor{\textquoteright}s experience by recommending exhibits of interest, and personalising the delivered content. The first step in this recommendation process is the accurate prediction of a visitor{\textquoteright}s activities and preferences. In this paper, we present two adaptive collaborative models for predicting a visitor{\textquoteright}s next locations in a museum, and an ensemble model that combines their predictions. Our experimental results from a study using a small dataset of museum visits are encouraging, with the ensemble model yielding the best performance overall.",
author = "Fabian Bohnert and Ingrid Zukerman and Shlomo Berkovsky and Timothy Baldwin and Liz Sonenberg",
year = "2008",
doi = "10.1007/978-3-540-70987-9_7",
language = "English",
isbn = "9783540709848",
series = "Lecture Notes in Computer Science",
publisher = "Springer, Springer Nature",
pages = "42--51",
editor = "Wolfgang Nejdl and Judy Kay and Pearl Pu and Eelco Herder",
booktitle = "Adaptive Hypermedia and Adaptive Web-Based Systems",
address = "United States",
note = "5th International Conference on Adaptive Hypermedia and Adaptive Web-Based Systems, AH 2008 ; Conference date: 29-07-2008 Through 01-09-2008",
}