Semantic++ Electronic Commerce Architecture and Models in Cloud

Author:

Zhang Guigang1,Li Chao2,Zhang Yong2,Xing Chunxiao2,Xue Sixin3,Liu Yuenan4

Affiliation:

1. Chinese Academy of Sciences, China & Tsinghua University, China

2. Tsinghua University, China

3. Tsinghua University, China & Renmin University, China

4. Renmin University, China

Abstract

Electronic commerce is playing a more and more important role in today's commercial activities. In this chapter, the authors propose a kind of new electronic commerce architecture in the cloud and give two kinds of new electronic commerce models. This chapter opens the discussion of why we need to design a new architecture in the cloud environment. Firstly, the authors have a discussion about the semantic++ computing. After the discussion, they give the architecture that can satisfy the requirements in the cloud. This architecture mainly includes five technologies, which are the massive EC data storage technology in the cloud, the massive EC data processing technology in the cloud, the EC security management technology in the cloud, OLAP technology for EC in the cloud, and active EC technology in the cloud. Then, the authors propose two kinds of semantic++ electronic commerce models based on big data. These two models are the new electronic commerce models. The first model is semantic++ electronic commerce Q/A (Questions/Answers) model and another is the active semantic++ electronic commerce model. These two models are all based on big data. Finally, the authors conclude this chapter and give future work.

Publisher

IGI Global

Reference52 articles.

1. Abouzeid, A., Bajda, K., & Abadi, D. (2009). HadoopDB: An architectural hybrid of MapReduce and DBMS technologes for analytical workloads. In Proceedings of VLDB2009 (pp. 922-933). VLDB.

2. Aliresearch, C. (2011). Across the critical point: 2011 annual net development research report. Retrieved October 1, 2012, from http://www.aliresearch.com/index.php?m-cms-q-view-id-68642.html

3. Amazon, C. (2009). Amazon SimpleDB getting started guide API version. Retrieved September 2, 2012, from http://docs.amazonwebservices.com/AmazonSimpleDB/latest/GettingStartedGuide/Welcome.html

4. Astrahan, M. M. (1976). System R: Relational approach to database management. ACM Transactions on Database Systems, 1(2), 97-137.

5. Avinash, L., & Prashant, M. (2010). Cassandra - A decentralized structured storage system. ACM SIGOPS Operating Systems Review, 44(2), 35-40.

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