In this paper, a new scheme for personalized web page recommendation using multi-user search engine query information is proposed. Our contribution is a scheme that improves the accuracy of personalization for various types of contents (e.g., documents, images and music) without increasing user burden. The proposed scheme combines “preference footprints” for browsed pages with collaborative filtering. We acquire user interest using words that are relevant to queries submitted by users, attach all user interests to a page as a footprint when it is browsed, and evaluate the relevance of web pages in relation to words in footprints. The performance of the scheme is evaluated experimentally. The results indicate that the proposed scheme improves the precision and recall of previous schemes by 1%-24% and 80%-107%, respectively.

This paper proposes a fast and scalable traffic monitoring system called Fast xFlow Proxy. For efficiently provisioning and operating networks, xFlow such as IPFIX and NetFlow is a promising technology for visualizing the detailed traffic matrix in a network. However, internet protocol (IP) packets in a large carrier network are encapsulated with various outer headers, e.g., layer 2 tunneling protocol (L2TP) or multi-protocol label switching (MPLS) labels. As native xFlow technologies are applied to the outer header, the desired inner information cannot be visualized. From this motivation, we propose Fast xFlow Proxy, which explores the complicated carrier's packet, extracts inner information properly, and relays the inner information to a general flow collector. Fast xFlow Proxy should be able to handle various packet processing operations possible (e.g., header analysis, header elimination, and statistics) at a wire rate. To realize the processing speed needed, we implement Fast xFlow Proxy using the data plane development kit (DPDK) and field-programmable gate array (FPGA). By optimizing deployment of processes between DPDK and FPGA, Fast xFlow Proxy achieves wire rate processing. From evaluations, we can achieve over 20 Gbps performance by using a single server and 100 Gbps performance by using scale-out architecture. We also show that this performance is sufficiently practical for monitoring a nationwide carrier network.