Data management is a crucial aspect in the Internet of Things (IoT) on Cloud. Big data is about the processing and analysis of large data repositories on Cloud computing. Big document summarization method is an important technique for data management of IoT. Traditional document summarization methods are restricted to summarize suitable information from the exploding IoT big data on Cloud. This paper proposes a big data (i.e., documents, texts) summarization method using the extracted semantic feature which it is extracted by distributed parallel processing of NMF based cloud technique of Hadoop. The proposed method can well represent the inherent structure of big documents set using the semantic feature by the non-negative matrix factorization (NMF). In addition, it can summarize the big data size of document for IoT using the distributed parallel processing based on Hadoop. The experimental results demonstrate that the proposed method can summarize the big data document comparing with the single node of summarization methods.

As increasing services with mobile devices, authentication technology by mobile devices has diversified. Nowadays to cope with security threat of e-commerce high rick transactions need multi-factor authentication technology conjoined in one or more factors. This paper proposes 2-factor authentication technology for security enhancement in electrical micro-payment system.

Abstract

In this paper, a Prototype design of electronic coupons ecosystem using NFC (Near Field Communication) in smart phones with OMM (Object Memory Model) is presented. The goal of OMM is to support the life cycle of NFC-based Electronic Coupon ecosystem for profile and usage, from E-Coupon push service and to E-Coupon clearance, using smart phone based on NFC devices. We propose the E-Coupon with OMM based on NFC, and present software design of E-Coupon among server and users.

Recently various studies on recommendation systems based on the expert knowledge are actively conducted in the fusion research of IT field. Present systems recommend same items to everyone based on the knowledge of common experts group. While this paper suggests to show expert recommendations and researcher ideas based on the big-data analysis of existing research findings and designs the system for users possible to metaanalysis by comparing research findings. Therefore this paper proposes the fabric pattern recognition search system which can show various views of experts.