The problem of mobile sequential recommendation is to suggest a route connecting a set of
pick-up points for a taxi driver so that he/she is more likely to get passengers with less travel …

We speed up the solution of the mobile sequential recommendation (MSR) problem that
requires searching optimal routes for empty taxi cabs through mining massive taxi GPS data …

We enhance the mobile sequential recommendation (MSR) model and address some
critical issues in existing formulations by proposing three new forms of the MSR from a multi …

The classic mobile sequential recommendation (MSR) problem aims to provide the optimal
route to taxi drivers for minimizing the potential travel distance before they meet next …

The acquisition and analysis of large amounts of mobile trajectory data promote the rapid
development of mobile recommender systems, which can essentially recommend a series of …

A theory is developed to unify the original form, and its many variations, of the mobile
sequential recommendation (MSR) problem. The unified theory, expressing the same MSR …

With the increasing availability of moving-object tracking data, use of this data for route
search and recommendation is increasingly important. To this end, we propose a novel …

The increasing availability of large-scale location traces creates unprecedent opportunities
to change the paradigm for knowledge discovery in transportation systems. A particularly …

Multi-behavior sequential recommendation (MBSR), which models multi-behavior
sequentiality and heterogeneity to better learn users' multifaceted intentions has achieved …

Within online platforms, it is critical to capture the semantics of sequential user behaviors for
accurately predicting user interests. Recently, significant progress has been made in …