Dynamic path prediction and recommendation in a museum environment

Abstract

This research is concerned with making recommendations to museum visitors based on their history within the physical environment, and textual information associated with each item in their history. We investigate a method of providing such recommendations to users through a combination of language modelling techniques, geospatial modelling of the physical space, and observation of sequences of locations visited by other users in the past. This study compares and analyses different methods of path prediction including an adapted naive Bayes method, document similarity, visitor feedback and measures of lexical similarity.