A Broad Learning Approach for Context-Aware Mobile Application Recommendation

With the rapid development of mobile apps, the availability of a large number of mobile apps in application stores brings challenge to locate appropriate apps for users. Providing accurate mobile app recommendation for users becomes an imperative task. Conventional approaches mainly focus on learning users' preferences and app features to predict the user-app ratings. However, most of them did not consider the interactions among the context information of apps. To address this issue, we propose a broad learning approach for \textbf{C}ontext-\textbf{A}ware app recommendation with \textbf{T}ensor \textbf{A}nalysis (CATA). Specifically, we utilize a tensor-based framework to effectively integrate user's preference, app category information and multi-view features to facilitate the performance of app rating prediction. The multidimensional structure is employed to capture the hidden relationships between multiple app categories with multi-view features. We develop an efficient factorization method which applies Tucker decomposition to learn the full-order interactions within multiple categories and features. Furthermore, we employ a group $\ell_{1}-$norm regularization to learn the group-wise feature importance of each view with respect to each app category. Experiments on two real-world mobile app datasets demonstrate the effectiveness of the proposed method

Process of social integration: the key to making enterprise systems-enabled change

Most previous enterprise systems (ES) studies focus on the ES implementation issues or critical success factors without taking into consideration that complex relationship of reciprocal causality between technology and human factors would cause the failure of ES to meet organizational expectations or deliverance of values promised. In this study, we try to understand the concept of social integration (SI) through exploring the use of ES in supporting organizational daily operations. In our in-depth case study of Talam, 40 interviews were collected from a company with ten years of experience in the management and application of ES. We have successfully identified six social integration processes and three social integration mechanisms that help to explain the interrelationship of the dynamic nature of social integration