Network appointment sharing traveler matching method based on network representation learning

Abstract

The invention discloses a network representation learning-based multiplication-sharing matching method. According to the relation between the starting point and the end point of the passenger and theoriginal path of the driver, the ride sharing is divided into two types, the first type is end point sharing, the other type is path sharing, the passenger needs to walk from the starting point to theboarding point, then sharing is achieved, then the passenger walks from the boarding point to the destination, and the path track of the sharing is one part of the path track of the passenger; a heterogeneous multiplication network is constructed, and representation learning is performed on the heterogeneous multiplication network by using a network representation learning model to obtain low-dimensional vector representation of the user node; and the cosine similarity between the driver and the passenger nodes is calculated, the calculated cosine similarity values are sorted from large to small, and the first k passengers with the highest similarity values with the driver are returned as passengers capable of sharing the passengers to achieve sharing. Compared with a traditional method which only uses distance recommendation, the ride sharing recommendation method provided by the invention is more reliable, the semantic comprehensiveness is visual, potential carpooling users can be accurately discovered, and faster and more convenient services are provided for the ride sharing users.

Description

technical field [0001] The invention belongs to the field of group recommendation, and in particular relates to a method for matching online booking and sharing travel personnel based on network representation learning. Background technique [0002] With the increasing development of online car-hailing platforms and APPs, shared travel is gradually recognized and accepted by the public. At the same time, with the development of related travel technologies, such as travel route matching, travel group discovery, route planning, travel behavior analysis and other related work According to research, carpooling has also become a convenient and feasible travel mode. The research on ride-sharing matching can provide users with better travel experience and higher travel efficiency. [0003] Network representation learning and the use and impact of ride-sharing have drawn a lot of attention to the research of ride-sharing matching methods. In the research of ride-sharing matching, ...

AI Technical Summary

Problems solved by technology

Traditional matching methods only rely on the geographical distance between passengers and drivers, and do not take into account the relationship between passengers or drivers and other features, such as the relationship between traveler and destination, time

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