A museum guide and knowledge recommendation method based on a cultural relic knowledge map

Abstract

The invention discloses a museum cultural relic guide and knowledge recommendation method based on a knowledge graph. The method comprises the steps that firstly, a word segmentation tool and a regular expression conversion rule are used for converting natural language query input by a user into SPARQL query statements, cultural relic knowledge query and reasoning are carried out in a SPARQL language mode, and the queried cultural relics are visually presented to the user in a knowledge graph mode; meanwhile, through recommendation algorithms such as cultural relic attribute association and collaborative filtering, cultural relics or cultural relic background knowledge related to currently inquired cultural relics are recommended to the user for the interested user to select and browse ina knowledge graph mode. The method can interact with the user through the natural language based on the constructed cultural relic knowledge map, recommend other cultural relics related to the currentcultural relic or possibly interested by the user to the user, guide the user to better browse cultural relic information and understand related cultural relic knowledge.

Description

technical field [0001] The present invention relates to the field of knowledge maps, and more specifically relates to a museum guide and knowledge recommendation method based on cultural relics knowledge maps. Background technique [0002] In recent years, with the improvement of people's living standards, more and more people choose to travel to increase their knowledge and cultivate their sentiments. As an elegant cultural tourist destination, museums are becoming more and more popular among tourists. However, there are many cultural relics exhibited in the museum, and tourists cannot directly obtain the information of the cultural relics they are interested in. Therefore, the method of applying knowledge graphs to museum guides has emerged as the times require, which can further help tourists visit museums to appreciate cultural relics. In addition, the technology in this field The personnel also use the content association algorithm and the collaborative filtering algori...

AI Technical Summary

Problems solved by technology

[0003] However, there are still big problems in the navigation methods and recommendation methods existing in the prior art. Among them, the navigation method cannot recognize and query people's natural language, which is far from meeting the requirements of intelligent query in today's era. Moreover, in the recommendation method, the content association algorithm cannot be adjusted according to the user's preferences. The collaborative filtering algorithm requires a large amount of cold start data when the user uses it less frequently, which may easily cause data loss and cause unnecessary problems.

[0004] Therefore, on the basis of establishing a good knowledge map, how to improve the query method so that it supports query using natural language, and how to solve the cold start of the recommendation method in the existing technology and cannot be adjusted according to preferences to improve the use and use of tourists. The problem of viewing experience is an urgent need for those skilled in the art to solve

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