Estimating point-of-interest rating based on visitors geospatial behaviour

Matej Senožetnik^{1, 2}, Luka Bradeško^{1, 2}, Tine Šubic¹, Zala Herga^{1, 2}, Jasna Urbančič¹, Primož Škraba¹ and Dunja Mladenić^{1, 2}

Institut Jožef Stefan
Jamova 39, 1000 Ljubljana
name.surname@ijs.si
Jožef Stefan International Postgraduate School
Jamova cesta 39, 1000 Ljubljana

Abstract

Rating of different services, products and experiences plays an important role in our digitally assisted day-to-day life. It helps us make decisions when we are indecisive, uninformed or inexperienced. Traditionally, ratings depend on the willingness of existing customers to provide them. This often leads to biased (due to the insufficient number of votes) or nonexistent ratings. This was the motivation for our research, which aims to provide automatic star rating. The paper presents an approach to extracting points-of-interest from various sources and a novel approach to estimating point-of-interest ratings, based on geospatial data of their visitors. Our research is applied to campsite dataset where the community is still developing and more than thirty percent of camps are unrated. Our study use case addresses a realword problem of motorhome users visiting campsites in European countries. The dataset includes GPS traces from 10 motorhomes that were collected over a period of 2 years. To estimate star ratings of points-of-interest we applied machine learning methods including support vector machine, linear regression, random forest and decision trees. Our experimental results show that the duration of visit, which is a crucial part of the proposed approach, is an indicative feature for predicting camp ratings.

Key words

machine learning, geospatial analysis

Digital Object Identifier (DOI)

https://doi.org/10.2298/CSIS171212011S

Publication information

Volume 16, Issue 1 (January 2019)
Year of Publication: 2019
ISSN: 2406-1018 (Online)
Publisher: ComSIS Consortium

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How to cite

Senožetnik, M., Bradeško, L., Šubic, T., Herga, Z., Urbančič, J., Škraba, P., Mladenić, D.: Estimating point-of-interest rating based on visitors geospatial behaviour. Computer Science and Information Systems, Vol. 16, No. 1, 131-154. (2019), https://doi.org/10.2298/CSIS171212011S