Commuting passenger social recommendation method and platform based on urban public transport trip big data

Abstract

The invention discloses a commuting passenger social contact recommendation method based on urban public transportation travel big data. The method comprises the following steps: extracting urban public transportation travel data of each passenger; selecting an appropriate grid granularity, and carrying out grid division on the urban public transport coverage area; identifying commuting passengersin all urban public transportation passengers by utilizing the travel behavior characteristics of the commuting passengers; carrying out similarity calculation on the commuting time, the commuting place and the interest type of any two commuting passengers in the commuting passenger sequence so as to obtain the similarity between the commuting passengers; determining a commuting passenger similarity sequence of the commuting passengers, and arranging the commuting passengers according to the similarity; and performing social recommendation on all commuting passengers according to the similarity sequence. The invention further discloses a social recommendation platform, real urban public transport data are utilized, a novel social mode is effectively provided according to the travel behaviors of the commuting passengers, and the social recommendation platform is used for meeting the social demands of modern people for standing on the living circle and the working circle.

Description

technical field [0001] The invention belongs to the field of intelligent transportation, and in particular relates to a commuter passenger social recommendation method based on urban public transport travel big data, and also relates to a commuter passenger social recommendation platform. Background technique [0002] With the rapid development of the economy, people's living standards are improving day by day. At the same time, a series of problems such as the accelerated pace of life, increased survival pressure, and weak interpersonal relationships have also arisen. In an era of increasingly material abundance, urbanites are paying more and more attention to the quality of their spiritual life, and their social needs are becoming stronger. However, in the Internet era, phenomena such as Internet scams and mobile phone dependence seem to intensify the "social island" effect. This phenomenon is particularly evident in large cities, where severe separation of occupation and...

AI Technical Summary

Problems solved by technology

[0005]Aiming at the problem that social recommendation lacks the use of residents’ travel behavior to construct resident portraits, it is necessary to propose a new social recommendation method for commuters based on urban public transport travel data, which can effectively Solve the phenomenon of "social islands" during commuting

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