Abstract
Now-a-days, social and professional networks have become main focus of interest for the research community to extract useful information. Many researchers have explored different features of social networks which help the experts to make discoveries in an easy way. LinkedIn is a professional network and there are more than one hundred millions of registered users on the LinkedIn. These users have different kinds and levels of expertise in various domains. Although the data available on the LinkedIn is in semi-structured form, however, still it’s a big challenge for the organizations to find the required expertise in such huge collection of data. In this paper, we proposed an automated technique which collects structured information from the LinkedIn profiles. An innovative algorithm has been designed and developed which ranks professionals based on their expertise level according to user selected criteria. Our proposed methodology (“Float Search”) also provides a user-friendly interface and an interactive visualization of the experts. Float Search also provides option for users to weight each required expertise according to their preferences. Results of Float Search have been compared with that of LinkedIn search and evaluated through user study. The results show that 70.49% of the reviewers considered our ranking approach better and 28.35% reviewers regarded it as the best approach for searching required experts.
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Iqbal, M., Ahmad, M. (2019). Ranking and Visualization of Experts for Communication Using Linkedin. In: Arai, K., Bhatia, R., Kapoor, S. (eds) Proceedings of the Future Technologies Conference (FTC) 2018. FTC 2018. Advances in Intelligent Systems and Computing, vol 881. Springer, Cham. https://doi.org/10.1007/978-3-030-02683-7_1
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DOI: https://doi.org/10.1007/978-3-030-02683-7_1
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