Research and Development of User Clustering-Based Content Similarity Algorithms in Dance-Assisted Choreography Techniques

Abstract

With the gradual development of digital information and software computing capabilities, the use of computers in dance-assisted choreography is becoming more and more widespread. But although the level of computers is now in rapid development, the technical level of using computers in dance choreography is not yet very mature, technical support is not in place, dance-assisted choreography is not effective, and the existing technical level is not yet able to meet the new needs of dance choreography. In order to improve the dance-assisted choreography technology and provide a more complete educational user interface for dance-assisted choreography, the content similarity algorithm of user clustering has a wide range of operations and a strong ability to calculate the amount of data, combined with the computer to apply the content similarity algorithm of user clustering in dance-assisted choreography technology to build a dance-assisted choreography system based on user clustering. The article proposes three major methods based on collaborative filtering algorithm of user clustering, collaborative filtering algorithm based on similarity class and user preference, and fuzzy cluster analysis of users and analyses their principles. In the experimental part, the performance of IBCF algorithm and collaborative filtering algorithm in dance-assisted choreography system is compared and analysed to observe the change of MAE value under the change of user similarity with number under different k values of cluster classes. The experimental results found that the MAE values of the IBCF algorithm and the collaborative filtering algorithm in the system were at 0.84 and 0.76, respectively, with a difference of about 8% between the two MAE values. The smaller the MAE value, the higher the effectiveness in the dance-assisted choreography technique. Applying the clustering algorithm to the system to make local adjustments and analysis of dance movement paths, it can grasp the choreography rules more precisely and innovate the choreography techniques.

Retracted: Research and Development of User Clustering‐Based Content Similarity Algorithms in Dance‐Assisted Choreography Techniques

“…Tis article has been retracted by Hindawi following an investigation undertaken by the publisher [1]. Tis investigation has uncovered evidence of one or more of the following indicators of systematic manipulation of the publication process:…”

“…This article has been retracted by Hindawi following an investigation undertaken by the publisher [ 1 ]. This investigation has uncovered evidence of one or more of the following indicators of systematic manipulation of the publication process: Discrepancies in scope Discrepancies in the description of the research reported Discrepancies between the availability of data and the research described Inappropriate citations Incoherent, meaningless and/or irrelevant content included in the article Peer-review manipulation …”