Users become less and less patient with huge useless data today. One of the great challenges now most net searching engines meet is how to get valuable information from lots of data sets. Aiming to satisfy every user’s special demand, we need to integrate and optimize the whole course of data searching, including adjusting the users’ input keywords, searching original results from network, and further processing of these results. Learning from the idea of Supply Chain Management, we put forward the concept of Information Supply Chain (ISC) in this paper to generalize the course above .For ISC’s optimization, artificial neural network is chosen as a tool to find out the relationships between different keywords and paper categories, which are summarized and stored in knowledge base. Based on it, the process of selecting proper keywords and searching news information could be more efficient. A pruning method named MW-OBS is illustrated to train ANN as well. Some details about the framework and components are also mentioned, especially on how an individual step in ISC works, what’s the relationship between them, and how they coordinate to meet every personal demand. ISC, an integrated information processing in the interests of users’ individual need, has great advantages over simple searching from network with original keywords.
Li, Qian; Wang, Yongxian; and Zhu, Youqin, "Study of Information Supply Chain and Artificial Neural Network’s Related Application" (2004). ICEB 2004 Proceedings (Beijing, China). 60.