Abstract
Recently, a search system has been a trend of personalization such as recommendation systems and social searches. Because, each users receive different results for the same queries by using user preference and interesting. Specially, a social relation is a most important factor of search system, and therefore, many recommender system using have been proposed. However, existing recommender systems typically return a set of search results based on a user’s query without considering user interests and preference. Therefore, the identical query from each user will generate the same set of results displayed in the same way for all users. To overcome this restriction, this paper proposes a recommender system based on personalized search using intimacy in SNS and describe a prototype of our recommender system.
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Acknowledgments
This research was supported the Next-Generation Info. Computing Dev. Program through the NRF of Korea funded by the Ministry of Science, ICT & Future Planning (2015R1C1A1A02036442). The corresponding author is Bongjae Kim.
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Kim, JD., Kim, B., Park, JH. (2017). Implementation of Recommender System Based on Personalized Search Using Intimacy in SNS. In: Park, J., Pan, Y., Yi, G., Loia, V. (eds) Advances in Computer Science and Ubiquitous Computing. UCAWSN CUTE CSA 2016 2016 2016. Lecture Notes in Electrical Engineering, vol 421. Springer, Singapore. https://doi.org/10.1007/978-981-10-3023-9_111
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DOI: https://doi.org/10.1007/978-981-10-3023-9_111
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