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Generating Social Relationships from Relational Databases for Graph Database Creation and Social Business Intelligence Management

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Intelligent Computing (SAI 2018)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 858))

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Abstract

Social media services create an extremely exciting global network, together with a burst of knowledge regarding product information, marketing solicitation or public issues discussion. The community is becoming an influential repository for the analysis of counter-terrorism, human resource management, marketing, service design and any other kinds of business activities. However, the collection of social relationships between individuals, among places or even objects is a daunting task. Therefore, we need an effective way to generate pre-existed relationships as a basis for the analysis of social networks. In this paper, we propose a framework for generating relationships from traditional relational databases, which have been tremendously employed to store commercial data, including customers, staffs, and other related stuffs. We explore the processes of generating explicit and implicit relationships from the viewpoint of Entity-Relationship Model, where the former can be derived directly from the E-R schema, and the latter can be generated from the viewpoint of data semantics. The derivation can be conducted by defining rules, expressing pattern matching in query statements, or even applying data mining algorithms. The obtained result can be used as a stem to evolve to connect the social networks of customers, product manufacturers and related staffs. Based on our framework, the constructed graph database can be easily linked to traditional relational technologies, including data warehouses, knowledge management or business intelligence. Our framework provides a progressive evolution from relational database to graph database, with the pre-existed applications to link with social intelligence seamlessly. We believe this framework helps us pave a way for developing people-centric technologies for the needs of social resource integration and social business intelligence in every domain.

This research is supported by the Ministry of Science and Technology, Taiwan, ROC, under Contract No. MOST 107-2410-H-992-016-MY2.

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Acknowledgment

This research is supported by the Ministry of Science and Technology, Taiwan, ROC, under Contract No. MOST 107-2410-H-992-016-MY2.

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Authors and Affiliations

  1. Department of Information Management, National Kaohsiung University of Science and Technology (First Campus), Kaohsiung, Taiwan, ROC

    Frank S. C. Tseng

  2. Department of Computer and Information Science, ROC Military Academy, Kaohsiung, Taiwan, ROC

    Annie Y. H. Chou

Authors
  1. Frank S. C. Tseng
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  2. Annie Y. H. Chou
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Corresponding author

Correspondence to Frank S. C. Tseng .

Editor information

Editors and Affiliations

  1. Faculty of Science and Engineering, Department of Information Science, Saga University, Honjo, Saga, Japan

    Kohei Arai

  2. The Science and Information (SAI) Organization, Bradford, West Yorkshire, UK

    Supriya Kapoor

  3. The Science and Information (SAI) Organization, Bradford, West Yorkshire, UK

    Rahul Bhatia

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Tseng, F.S.C., Chou, A.Y.H. (2019). Generating Social Relationships from Relational Databases for Graph Database Creation and Social Business Intelligence Management. In: Arai, K., Kapoor, S., Bhatia, R. (eds) Intelligent Computing. SAI 2018. Advances in Intelligent Systems and Computing, vol 858. Springer, Cham. https://doi.org/10.1007/978-3-030-01174-1_28

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