Location-Based Service Insights: A Comprehensive Review of Data Mining Objects

Location-based services are increasingly popular across diverse industries, spanning transportation, logistics, and tourism. Extensive studies have delved into this field, exploring facets such as application, performance enhancement, and security vulnerabilities that may endanger users. This systematic literature review, encompassing the years 2020 to 2024 and sourced from IEEE Xplore, investigates the prevalent objects and data types in location-based services. The paper's methodology for selecting articles extends beyond search keywords, incorporating advanced terms from abstracts. This dual criteria led to the identification of fifty papers based on abstract keywords. The systematic review categorized papers based on objects and data, revealing seven research categories: privacy protection data, urban planning, POI data, mobility, farming, tourism, and indoor maps. Data types were classified into two groups: social media data and non-social media data. The analysis reveals that effective utilization of location-based data is pivotal in enhancing various facets of daily life, streamlining processes, and contributing to more informed decision-making. However, the study also highlights the imperative need to address data privacy concerns vigilantly. By shedding light on these aspects, this paper aims to contribute to the ongoing discourse in the field of LBS, emphasizing the balance between technological advancement and ethical data handling.