Air ticket personalized recommendation method based on shared account passenger prediction

Abstract

The invention provides an air ticket personalized recommendation method based on shared account passenger prediction. The method includes the steps of 1. counting all of the orders under each account and analyzing the preference of a user on different air ticket attributes, and calculating the weight of the user corresponding to each attribute based on the user historical orders; 2. calculating the probability distribution of all of the passengers under the account according to the account historical behaviors and current conversation context; and 3. ordering from high to low according to the similarity between the search result and the preference model combined with passenger prediction, recommending the first K results to the users, wherein K is an integer. The recommendation method based on the shared account user prediction takes the probability distribution of the passengers to obtain a targeted recommendation result. The method provided is high in universality, if the method is needed to be applied to a new filed, one only needs to redefine the attribute characteristics through the combination with the filed knowledge, and a composite preference model based on the user probability distribution is constructed, so that the recommendation effect can be effectively improved.

Description

technical field [0001] The invention relates to the technical field of personalized recommendation, in particular to a method for personalized recommendation of airline tickets based on passenger prediction of shared accounts. Background technique [0002] In today's era of information explosion, the main purpose of personalized recommendation technology is to extract user preferences according to user behavior, and provide users with suggestions on obtaining information accurately and efficiently. Personalized recommendations can effectively anticipate the needs of users, reduce the cost of obtaining information for users, make the interaction process more efficient and improve user experience. Therefore, it is widely used in various service websites including e-commerce, news portals, and multimedia. There will also be major recommended technology competitions and academic conferences every year. Personalized recommendation has become an indispensable technology in the I...

AI Technical Summary

Problems solved by technology

There may be passenger-shared account situations where the account purchases tickets for several passengers, and preferences may vary among these passengers

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