IGA-SOMK + + : a new clustering method for constructing web user profiles of older adults in China

Mining user data and constructing web user profiles of older adults from the perspective of elderly services is conducive to understanding their behavioral habits, needs, and usage preferences on the web, which provides more targeted elderly care services. In this paper, IGA-SOMK + + , which is a novel clustering method for constructing web user profiles of older adults, is proposed based on the China Family Panel Studies (CFPS) survey data, which include 6596 older adults aged greater than 60 years. The selected data aspects include basic information, work situation, health situation, living habits, and web use services. To describe the web user profiles of older adults, a hybrid method based on improved genetic algorithm (IGA) feature selection, self-organizing feature maps (SOM), and K-means + + is proposed. Data on older adults’ web use behaviors are first processed, and IGA is used for feature selection based on the adaptive crossover and mutation probabilities. SOM is then used to determine the initial center vectors of K-means + + for further clustering, which is referred to as SOMK + + (SOM-K-means + +). The results of IGA-SOMK + + are compared with those of the state-of-the-art methods, including the K-means, mini batch K-means, Agnes, K-modes, FCM, K-means + + , SOMK + + , and IHPSO-KM. In addition, the significance and robustness of IGA-SOMK + + are analyzed. The experimental results show that the IGA feature selection reduces the influence of the redundant feature factors and improves the performance of the clustering algorithm. SOMK + + overcomes the sensitivity of K-means to initial cluster centers. Moreover, IGA-SOMK + + has the best clustering effect among the compared algorithms in terms of silhouette coefficient (SC), calinski-harabaz (CH) index, and davies-bouldin (DB) metrics. For example, it increases the SC from 0.280 to 0.629. Finally, by analyzing the results, the user group of older adults is segmented to perform the deep mining of CFPS data, which verifies the feasibility of the user profile model. This paper summarizes the basic situation of the current web access of older adults in China in terms of web use services, as well as the importance of the web in their lives and in the information channels. It also provides suggestions for the current problems of older adults in accessing the web.