원문정보
초록
영어
The applications of new information and communication technologies in the exhibition industry provide lots of opportunities for improving value of exhibition service.
Especially exhibit organizers can help the visitors to find the information they are looking for through a recommender system using the ubiquitous technologies.
However, existing recommender systems in the ubiquitous exhibition environment can’ reflect a visitor’dynamic preference since that system utilizes information of the pre-inputted exhibit booths.
Therefore, we suggest recommendation methodology for tour guidance modeled by a Bayesian network in the ubiquitous exhibition environment. Bayesian networks can reflect a visitor’ dynamic preference on the exhibit booths over time. We expect that the proposed methodology contribute is stable and accurate to identify the visitor’ dynamic preference and to recommend the exhibit booth.
목차
1. Introduction
2. Related work
2.1 Recommender system in the exhibition environment
2.2 Recommender system using Bayesian network
3. Methodology
3.1 Overview
3.2 Preprocessing
3.3 Identification of visitors’ behavior trajectory
3.4 Computation of exhibit booth sequence probability
3.5 Similarity Computation
3.6 Generation of top-N exhibit booth recommendationlist
4. An illustrative example
4.1 Preprocessing
4.2 Identification of visitors’ behavior trajectory
4.3 Computation of exhibit booth sequence probability
4.4 Similarity Computation
4.5 Generation of top-N exhibit booth recommendationlist
5. Conclusion and future work
References