Tourism route recommendation method and system based on tourism knowledge graph

Abstract

The invention discloses a tourism route recommendation method and system based on a tourism knowledge graph. The method comprises the steps of obtaining scenic spot data and user comment data, carrying out data cleaning, and unifying data specifications; constructing an interaction information graph between the user and the scenic spot by using historical behavior data generated by the user for the scenic spot; constructing a scenic spot knowledge graph, forming a relational graph between scenic spots and scenic spot attributes, then importing data into a graph database, and displaying the constructed scenic spot knowledge graph in a visual form; constructing a collaborative knowledge graph with a high-order relationship by adopting the interaction information graph and the tourist attraction knowledge graph, and recommending tourist attractions conforming to the interest of the user through the collaborative knowledge graph; and carrying out tourist route planning on the recommended tourist attractions to obtain a complete tourist route. According to the invention, personalized scenic spot recommendation and route planning service can be provided for the user, and the recommendation result is more accurate and has interpretability.

Description

technical field [0001] The invention belongs to the field of travel services, and in particular relates to a travel route recommendation method and system based on a travel knowledge map. Background technique [0002] With the development of information technology and the Internet, people have gradually entered the era of information overload from the era of information scarcity. Recommendation system is one of the most effective ways to solve information overload. However, traditional tourism websites provide a large amount of data queries and relatively fixed travel routes, making it difficult to provide accurate recommendations for users, which greatly reduces the quality of travel services and the travel experience of travelers. Existing collaborative filtering algorithms have data sparsity and interpretability problems. It is considered that a set of historical items interacted by users has the same impact on users, and the contribution of all historical interactive it...

AI Technical Summary

Problems solved by technology

[0003] The purpose of the present invention is to solve the problem of low accuracy of tourist attraction recommendation and route planning in the above-mentioned prior art, to provide a tourist route recommendation method and system based on the tourist knowledge map, which can recommend scenic spots that better meet individual preferences for users , to plan the best travel route, and the recommendation results are more accurate and interpretable

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