Improvement of a location-aware recommender system using volunteered geographic information

Abstract

Recommender systems (RS), as supportive tools, filter information from a massive amount of data based on the determined preferences. Most of the RS require information about the context of users such as their locations. In such cases, location-aware recommender systems (LARS) can be employed to suggest more personalized items to the users. The most current research projects on LARS focus on the development of algorithms, evaluation methods and applications. However, the role of up-to-date spatial databases in LARS is not a well-researched area. The up-to-date spatial information would potentially improve the accuracy of items which are recommended by LARS. Volunteered geographic information (VGI) could be a low-cost source of up-to-date spatial information for LARS. This article proposes an approach to enrich spatial databases of LARS by VGI. Since not all records of VGI are fitted for use in LARS, a mechanism is developed to identify useful information. Some VGI data sets refer to existing spatial data in the database while other VGI data sets are shared for the first time. Therefore, the proposed method assessed the quality of VGI with reference source (for VGI which is existed in the database) and VGI without reference source (for VGI which is shared for the first time). To demonstrate the feasibility of the proposed approach, a mobile application has been developed to recommend suitable restaurants to the users based on their geospatial locations. The evaluation of the method indicates that VGI can potentially enhance the functionality of the LARS in predicting the users’ interests.

KEYWORDS:

• Location-aware recommender system
• volunteered geographic information
• spatial data quality
• context-aware recommender system

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes

1 International Cartographic Association

2 Comité Européen de Normalisation/ Technical committee 287

3 International Standardisation Organisation / Technical committee 211

4 Spatial Data Transfer Standards

5 Information Technology

6 http://grouplens.org

7 http://fireflyz.com.my

8 http://grundylibrary.org

9 http://amazon.com

10 Institut Géographique National

11 http://fidilio.com

12 Since the application language was Farsi, users write these Farsi words which all are synonym to restaurant. In English case, users may write café or buffet.

13 Users’ reliability is the score that users get based on their previous contribution and information of their profile. Such information helps us to estimate quality of their next contribution.

14 Service Developer kit

15 Windows Communication foundation

16 DataBase Management System

17 In this method, users score recommended items by RS based on their similarity to their interests.