Design of cultural and creative experience products in scenic spots based on CORE model

Abstract

Under the background of “cultural and tourism integration”, scenic cultural and creative experience products are an important means to enhance the communication power of scenic spots and generate income. In this paper, the CORE model is used as the design concept, and the CORE design process for scenic cultural and creative products is constructed. The plain Bayesian classification algorithm is used to extract review feedback from the product, and the vectorization of the extracted reviews is achieved using the FastText model. The vectorized reviews are input into the logistic regression classification model to obtain sentiment classification results. A fused sentiment feature vector is constructed by combining Apirior and a sentiment dictionary aimed at separating sentiment vector classification. Finally, the experience effect of cultural and creative products is explored as an example of X scenic spot, and the optimization strategy of product design is explored. The attribute feature of X Scenic Spot’s cultural and creative experience product, “color” embraces four emotional attributes, and the corresponding adaptations are 4.77, 5.42, 5.40, and 5.38, respectively. The SDs of the emotional attributes of the existing product are The SDs of the emotional attributes of the existing products are 1.141, 1.025, and 0.184, respectively, and the differences between the product descriptions and the users’ opinions on the perceptual attributes are large, which provides the evaluation correlation in the CORE model. Under the guidance of the CORE model, four aspects of cultural and creative marketing, scenic area IP, consumer needs and product experience dimensions are proposed.

Keywords

• plain bayes
• fasttext model
• logistic regression
• sentiment vector
• core model
• 01a12