Towards the significance of taxi recommender systems in smart cities

Abstract

Since their launch in the early 1990's, recommender systems (RSs) have played an essential role in information filtering and providing personalized information to users by utilizing the web, mobile, context, personalized, and practical applications. Many research articles have been published in various application domains such as movies, books, documents, news, images, music, shopping, TV programs, tourism, group, social, taxi, and others. However, from these domains, taxi recommendation is a new and thrust area of research, as publications in this domain are few and recently published.Taxi recommendations are associated with drivers-passengers with their: behavior, hotspots, trajectory, point of interest, route planning or prediction, taxi finding, anomaly or fraud detection, urban computing, mobility patterns and so forth. Due to this diversity and various agendas in taxi recommendations, more exploration is required, as it is a less mature and growing field than other domains. So we have done a literature review in the taxi domain by classification, incorporating reputed articles published from 2001 to August 2022. We include the reputed papers which highlight, analyze and perform studies only on the taxi domain. This article categorizes and discusses the research and development in taxi recommendations as nature, approaches, algorithms, methods, datasets, models, devices, information, and evaluation techniques. This survey article will actively help the researchers and professionals understand the current situations in taxi RS and resolve future trends, opportunities, and research.

Guiding Urban Decision-Making: A Study on Recommender Systems in Smart Cities

“…The article written by Katarya [75] concentrated on an interesting topic that captures the reader's attention from the first paragraph. By providing an overview of the existing scientific literature around the area of taxi recommender systems in smart cities, published within a predefined timespan, more specifically, over a period of 22 years between 2001 and 2022, the author outlined interesting details about route planning, passengers' experiences, security, pricing, congestion, and many more.…”