Research On Indoor Path Planning With Intelligent Recommendation Characteristics

In recent years,the national economy has developed rapidly,and technology has brought a lot of convenience to people's lives,and the Internet has become one of the most convenient tools in people's daily lives.In various types of Internet applications,intelligent recommendation has been widely used as a technology with personalized characteristics.How to properly use recommendation algorithms to personalize services for users has practical application significance.Cultural tourism is one of the main methods of spiritual civilization construction.The use of recommendation algorithms can enhance the user's cultural experience.The research on indoor route recommendation in large museums can well solve the problem of personalized travel.This paper mainly studies the problem of applying the recommendation algorithm to the path planning of large indoor museums.Aiming at the problem of sparseness of the user's malicious rating and the scoring matrix of the recommendation algorithm,a collaborative filtering recommendation algorithm with item tag characteristics is proposed,and the user's tag preference characteristics are analyzed from the dimension of the tag attribute,and then collaborative filtering is performed to achieve the relic recommendation list The simulation results show that the collaborative filtering recommendation algorithm with item tag characteristics is more accurate than the traditional recommendation algorithm.Then,based on the location information of the exhibition room where the cultural relics are located,combined with the cultural relics recommendation list,calculate the indoor path nodes with recommended characteristics as the main basis for indoor path planning.After researching a variety of shortest path algorithms,it is proposed to use Dijkstra algorithm as the calculation method for path planning.According to the shortest path set of recommended path nodes,the nearest recommended nodes are connected in sequence from the starting point to obtain the indoor recommended path.Through simulation experiments The verification shows that indoor path planning with intelligent recommendation features can obtain personalized indoor walking routes,and implements a hierarchical strategy for multi-floor path planning.Finally,according to the above two methods,the functional requirements of the museum's indoor cultural relics tour route recommendation system are proposed.Through the system's outline design,the main functional modules of the system are realized.The software operation indicates that the collaborative filtering recommendation algorithm has the characteristics of item tags and intelligent The indoor path planning method with recommended characteristics has a good practical application effect.