Abstract
With the rapid growth of users in social networking websites, large amount of data are aggregated. Users are tending to find information through their friends on social network such as Facebook, and this behavior leads to a new search paradigm called social search. However, the traditional search engine like Google cannot handle this kind of search. The data cannot be indexed because of the membership privacy setting and social network relationships. Under this situation, it is harder and harder for users to search information related to their social network.
In this paper, we therefore proposed a system architecture which can deal with this issue and using the data from Facebook as example. An algorithm is also proposed which is the core technique of the system which is called Topic Participation Algorithm (TPA). Furthermore, we will propose a novel implemented social search engine which is developed based on the concept of social network analysis, data mining techniques and searching techniques.
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Yao, HR., Ting, IH. (2014). Topic Participation Algorithm for Social Search Engine Based on Facebook Dataset. In: Wang, L.SL., June, J.J., Lee, CH., Okuhara, K., Yang, HC. (eds) Multidisciplinary Social Networks Research. MISNC 2014. Communications in Computer and Information Science, vol 473. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-45071-0_13
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DOI: https://doi.org/10.1007/978-3-662-45071-0_13
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