[Li, Xiao-Yun; Yu, Ying; Ma, Jia-Yu; Yang, Xiao-Hua; Wan, Ya-Ping; Liu, Zhi-Ming; Jiang, Hui] School of Computer Science and Technology, University of South China, Hengyang, Hunan, China
Aimed to the inherent detects in present information retrieval service, this paper proposed an approach to exploit desktop context to provide personalized recommendation service. The files restored on the local disk and the documents opened in a work scenario were regarded as two separate parts serving for personalizing. The algorithm for extracting to desktop resources to build the long-term document model was introduced in detail, which further provides information to build a user's interest model. And the method to establish the short-term model in a work scenario to predict the user's curr...