Abstract
There is currently a number of interesting research works performed in the area of bridging the gap between Social Networks and Information Retrieval (IR). This is mainly done by enhancing the IR process with social information. Hence, many approaches have been proposed to improve the ranking process by personalizing it using social features. In this paper, we review some of these ranking functions.
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Bouadjenek, M.R., Bennamane, A., Hacid, H., Bouzeghoub, M. (2013). Evaluation of Personalized Social Ranking Functions of Information Retrieval. In: Daniel, F., Dolog, P., Li, Q. (eds) Web Engineering. ICWE 2013. Lecture Notes in Computer Science, vol 7977. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-39200-9_24
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DOI: https://doi.org/10.1007/978-3-642-39200-9_24
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-39199-6
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