Volume XLII-4/W18
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-4/W18, 975–980, 2019
https://doi.org/10.5194/isprs-archives-XLII-4-W18-975-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-4/W18, 975–980, 2019
https://doi.org/10.5194/isprs-archives-XLII-4-W18-975-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

  19 Oct 2019

19 Oct 2019

DISCOVER POINTS OF INTEREST BASED ON USERS’ INTERNET SEARCHES THROUGH AN ONLINE SHOPPING WEBSITE

G. Shahriari Mehr1, M. R. Delavar2, C. Claramunt3, B. N. Araabi4, and M. R. A. Dehaqani4 G. Shahriari Mehr et al.
  • 1School of Surveying and Geospatial Engineering, College of Engineering, University of Tehran, Tehran, Iran
  • 2Center of Excellence in Geomatic Engineering in Disaster Management, School of Surveying and Geospatial Engineering, College of Engineering, University of Tehran, Tehran, Iran
  • 3Naval Academy Research Institute Lanveoc-Poulmic, BP 600, 29240 Brest Naval, France
  • 4School of Electrical and Computer Engineering, School of Engineering, University of Tehran, Tehran, Iran

Keywords: Internet behavior, Points of Interest, Marketing, Recommendation, Similarity, Context-awareness

Abstract. In recent years, the development of the Internet plays a significant role in human's daily activities. One of the most important effects of the Internet is the change in the process of shopping. The advent of online shopping leads to establish a new channel for customers to obtain information about their desired goods and demands. Although many customers collect information from online channel, they also wish to try and search for their required goods at the stores. Besides, discovering this data leads to a new source for spatial analysis to find the users’ interests. Therefore, we can consider this data as a contextual information source for spatial analysis or primary source for recommending points of interest (POIs). In this research, our aim is to discover a relation among the users' internet searches and the goods at the stores to recommend the best store to the users. Euclidean distance is used to calculate the similarity between users' searches and the available goods at the stores. The proposed method has been implemented in the city of Tehran, capital of Iran. The results show that the users’ internet search behavior plays an essential role in the recommendation system which provides stores to the users based on the similarity among the users’ internet searches and the available goods at the stores.