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Photographic images help customers perceive product information more accurately and clearly. A customer's perception of a particular product also influences their decision to purchase it. In the context of a hotel, guests evaluate digital hotel photos online during their booking decision process. While a large body of research has contributed to the understanding of how hotel online digital images shape hotel customer behaviour, little is known about the aesthetics, content, and composition of hotel images and their effects on booking decisions. In addition, previous research has routinely been criticised for having methodological limitations. These studies have routinely used surveys and experiments to explore how hotel pictures affect customer perception of the hotel and his/her booking intentions. Unlike prior studies, this research scopes a determination of the 'selling' properties pertinent to the hotel's digital images placed online on the hotel-themed websites with the application of the latest technologies pursuant to visual data mining, processing and analysis. This study employed Google's Inception v3 neural network as an AI solution for embedding and classifying hotel photo images with the further application of logistic regression and fuzzy cognitive mapping method. The results of the present study determined the hotel picture properties that may engender positive customer perception of the hotel and sequentially can precipitate hotel booking. The revealed 'selling' hotel image properties comprise (a) light and time of the photo shooting, (b) image colour scheme, (c) human presence, and (d) shooting angle. This study suggests a set of practical recommendations to hotel marketers to develop 'selling' photo images that generate hotel bookings online. The completed research is one of the first in the nascent literature stream in AI-powered computer vision solutions studies to determine the effects of photo aesthetics on online hotel bookings. [ABSTRACT FROM AUTHOR]

Today is an era of data "big bang"; Internet information technology is widely used in various fields of society. As an indispensable spiritual food in people's daily life, books are increasing in number and scale. In order to better manage book information, people have introduced data mining technology. Based on this, this article takes the research and application of data mining technology in book copyright information management decision-making system as the theme, explores the role of data mining technology in book copyright information management, and aims to provide reference for our country's book copyright information management and decision-making. This article first introduces the common algorithms of data mining technology and then elaborates on the advantages and effectiveness of the association rule method in data mining. Aiming at some defects of the original Apriori algorithm of the association rule method, an improved Apriori algorithm is proposed. After taking the library book information management system and database of a university in our province as the experimental research object, the performance gap between the two algorithms is compared through experiments, and it is concluded that when the number of transaction set item records is less than 1400, the Apriori algorithm performs better, and when the number of records in the transaction set is greater than 1400, the improved Apriori algorithm is obviously more advantageous. The research results show that the introduction and application of data mining technology make the information management of books more efficient and convenient, and it is more convenient for the management and decision-making of book copyright information. [ABSTRACT FROM AUTHOR]