Special issue on pervasive and ubiquitous solutions for cultural enrichment

Cultures and heritages have been preserved in archeological centers, museums, historical centers, art galleries and exhibitions, and cultural artifacts provide rich information and insight about the cultural developments, transformations, traditional and ethics. Applying pervasive and ubiquitous computing technologies to culture and heritage provide immense benefits but a host of complexities, and this special issue of Personal and Ubiquitous Computing focuses on recent and research the looks at pervasive and ubiquitous solutions for cultural enhancement. The aim of this special issue is to attract recent research and contributions of high-quality papers in the relevant topics. Based on the feedbacks of peer-reviewers, as well as the evaluations of editors, 33 papers are selected in this special issue from 74 papers. The 33 papers which cover broad topics are selected and briefly introduced as follows. In the paper “The Construction of Sports Culture Industry Growth Forecast Model Based on Big Data”, the feasibility of sports culture industry growth prediction based on big data theory from the perspective of data mining is analyzed, and a sport culture industry growth prediction model based on genetic neural network is proposed. The simulation results demonstrate that the genetic neural network can effectively improve the efficiency and accuracy of prediction and show strong robust in predicting the laws of sports culture industry. In the paper “Design on Intelligence Music System in the Cultural Center based on IoT”, a set of music intelligent system design scheme in the cultural center based on the IoT technology is proposed, which makes the music realize intelligent and efficient management. In the paper “Dynamic Pricing Analysis of Redundant Time of Sports Culture Hall Based on Big Data Platform”, the game relationship between profit and consumption intention of sports cultural hall is analyzed. A big data platform of the pricing model and using mathematical statistics and support vector machine is constructed. Compared with different pricing strategies, the overall profit of sports cultural hall has been greatly improved. In the paper “Personalized Recommendation of Film and Television Culture Based on Intelligent Classification Algorithm”, a new personalized recommendation algorithm for film and television culture based on intelligent classification algorithm is proposed. The experimental results show that the personalized recommendation algorithm based on intelligent classification algorithm improves the scoring accuracy by 0.15. In the paper “Study on Large-scale Crowd Evacuation Method in Cultural Museum Using Mutation Prediction RFID”, a large-scale crowd of cultural museum is taken as the studied object, and a large-scale crowd evacuation method based on the mutation theory of RFID is proposed. Through the experiment tests on typical scenes, the evacuation control problems of four groups of people are analyzed and discussed. The results prove that the evacuation method proposed in this paper can provide guidance for crowd evacuation in the cultural museum. In the paper “An Improved Density-Based Single Sliding Clustering Algorithm for Large Datasets in. the Cultural Information System”, a technique for using a Hybridized Single Sliding Centroid with Density-based Clustering (HSSCDC) to data mine cultural datasets on the cultural information system is introduced. Experimental validation shows that the proposed HSSCDC automatically * Wei Wei weiwei@xaut.edu.cn