Method and system for processing tourist grading data based on big data

Abstract

The invention relates to the field of data processing, in particular to a method and system for processing tourist grading data based on big data. The method and system are used to perform the following steps: page labeling: as an overall product page library; user judgment: judging whether the user is a new user or an old user; one push, randomly calling part of the page tags and pushing them to the user terminal; basic analysis: setting the User's initial classification; update push: combine the initial push list and the exception page label to generate a new basic page list, replace the original basic page list, and push it to the client; exception record: record the classification information of the exceptions browsed by the user; Big data analysis: Calculate the data proportion of each page set based on the number of pages in each page set; generate an iterative page list, and iteratively update the basic page list. The present invention makes up for the relatively single deficiency of the data sample through iterative correction of the push label, improves the accuracy of push, and improves the efficiency of data interaction.

Description

technical field [0001] The invention relates to the field of data processing, in particular to a big data-based tourist classification data processing method and system. Background technique [0002] In the tourism industry, there are diversity in the classification of tourism items and the preferences of users. For example, different users often have different preferences in tourism projects such as natural scenic spots, cultural scenic spots, leisure travel activities, and overseas travel. In order to better stay close to the consumption habits and consumption ability of users, existing online travel platforms and travel service agencies often collect and calculate big data based on users' browsing history, consumption history and related information, and use algorithms such as cluster analysis to analyze and analyze data. Make a portrait of each user, obtain parameters such as consumption preferences and consumption levels of each user, and push relevant product introduc...

AI Technical Summary

Problems solved by technology

[0003] However, with the strengthening of people's awareness of personal data protection and stricter supervision, the access to user's detailed location information, identity information and other information closely related to the user has been restricted. In terms of trends, such Information will no longer be actively collected in the future, so the only objects that can be analyzed by big data are the main indicators of users' search records, browsing records and consumption records on a single platform. Compared with the past, the accuracy of user portraits based on data has dropped significantly, resulting in a corresponding decrease in the accuracy of push content, reducing the efficiency of information interaction

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