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General Information
Dr. Lin Huang
Metropolitan State University of Denver, USA
It's my honor to take on the position of editor in chief of IJMLC. We encourage authors to submit papers concerning any branch of machine learning and computing.
IJMLC 2013 Vol.3(2): 190-194 ISSN: 2010-3700
DOI: 10.7763/IJMLC.2013.V3.300

Advanced Data Processing in the Business Network System

Daniel Ritter
Abstract—The discovery, representation and reconstruction of Business Networks (BN) from Network Mining (NM) raw data is a difficult problem for enterprises. This is due to huge amounts of e.g. complex business processes within and across enterprise boundaries, heterogeneous technology stacks, and fragmented data. To remain competitive, visibility into the enterprise and partner networks on different, interrelated abstraction levels is desirable. We show the query and data processing capabilities of a novel data discovery, mining and network inference system, called Business Network System (BNS) that reconstructs the BN - integration and business process networks - from raw data, hidden in the enterprises’ landscapes. The paper covers both the foundation and the key data processing characteristics features of BNS, including its underlying technologies, its overall system architecture, and data provenance approach.

Index Terms—Data processing, data provenance, information retrieval, network mining.

Daniel Ritter is with the Technology Development at the SAP AG, Walldorf, BW 69190, Germany (e-mail: daniel.ritter@sap.com).


Cite:Daniel Ritter, "Advanced Data Processing in the Business Network System," International Journal of Machine Learning and Computing vol. 3, no. 2, pp. 190-194, 2013.

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