Abstract
The social network services have tremendously grown during the recent years and have a promising future ahead. Many organizations are coming forward with wide variety of interesting social networking services. In fact, most of the social network services are almost identical and the users select the services based on public perceptions; trial and error method which sometimes provide lower level of satisfaction to the users. Therefore, discovering and providing the best social network service based on user’s interest is really a challenge. Discovering a set of feasible social services and selecting the most appropriate social network service based on the user preferences can be modeled as multi-criteria decision making problem. In this chapter, an effective framework for service selection of social network is proposed. The experimental results on overhead, social service deduction time, average delay have also been obtained. The results show that the proposed framework is effective.
Keywords
- Social Network Service (SNS)
- Organizational Social Networks
- Service Selection
- Aggregated Preference Indices
- Negative Outranking Flow
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Silas, S., Ezra, K., Rajsingh, E.B. (2012). An Effective User-Driven Framework for Selection of Social Network Services. In: Abraham, A. (eds) Computational Social Networks. Springer, London. https://doi.org/10.1007/978-1-4471-4051-1_10
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DOI: https://doi.org/10.1007/978-1-4471-4051-1_10
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