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Developing Geo-recommender Systems for Industry

  • Edith Verdejo-Palacios
  • Giner Alor-Hernández
  • Cuauhtémoc Sánchez-Ramírez
  • Lisbeth Rodríguez-Mazahua
  • José Luis Sánchez-Cervantes
  • Susana Itzel Pérez-Rodríguez
Chapter
Part of the Intelligent Systems Reference Library book series (ISRL, volume 120)

Abstract

Recommender systems are broadly used to provide filtered information from a large amount of elements. They provide personalized recommendations on products or services to users. The recommendations are intended to provide interesting elements to users. Nowadays, recommender systems and geolocation services have focused the attention of many users, this attention has produced a new kind of recommender system called Geo-recommender. Geo-recommender systems can successfully suggest different places depending on the users’ interest and current location. This characteristic is useful in market competition, since it allows a better analysis of the study of business locations. Geolocation is key factor to obtain the desired business success; while a business is closer to customers, the benefits are greater. In this chapter, we propose an integration architecture for developing geo-recommender systems for industry. Different case studies are described where the use of geo-recommender systems has taken relevance. The architecture proposed has a layered design, where the functionalities and interrelations of the layer components are distributed in order to ensure maintenance and scalability. Also, a geo-recommender system prototype called GEOREMSYS was developed as a proof of concept of the architecture proposed. GEOREMSYS uses collaborative filtering techniques by giving possible locations for Point of Sale (POS).

Keywords

Geographic Information System Recommender System Mobile Application Movie Theater Geographic Information System Tool 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgements

The authors are grateful to the National Technological Institute of Mexico for supporting this work. This research paper was sponsored by the National Council of Science and Technology (CONACYT), as well as by the Public Education Secretary (SEP) through PRODEP.

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Edith Verdejo-Palacios
    • 1
  • Giner Alor-Hernández
    • 1
  • Cuauhtémoc Sánchez-Ramírez
    • 1
  • Lisbeth Rodríguez-Mazahua
    • 1
  • José Luis Sánchez-Cervantes
    • 2
  • Susana Itzel Pérez-Rodríguez
    • 3
  1. 1.Division of Research and Postgraduate StudiesInstituto Tecnológico de OrizabaOrizabaMexico
  2. 2.CONACYT-Instituto Tecnológico de OrizabaOrizabaMexico
  3. 3.Universidad Popular Autónoma Del Estado de PueblaPueblaMexico

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