[Purpose/significance] User interest recommendation is an important content in information services. The context of current researches about information recommendation is considered as an independent factor but ignoring the relation in it. This paper combined the contextual relations into the recommending process and realized the user interest recommendation on the social media. [Method/process] This paper takes a hypothesis that users in the similar context may have similar interests to improve the original user interest network and achieve the recommendation:constructing the explicit and implicit network by the social network and the resources similarity; constructing the contextual network by the co-occurrence principle and the context similarity itself; calculating direct interest scores and indirect interest scores by the network transmission; realizing recommendation by using collaborative filtering. [Result/conclusion] The experiment shows that combing contextual relations into the recommendation process can not only expand users' social relationship, but also ameliorate recommendation results.
Fang Xiaoke
,
Yan Chengxi
. User Interest Recommendation by Combining Contextual Relations on the Social Media[J]. Library and Information Service, 2017
, 61(21)
: 99
-105
.
DOI: 10.13266/j.issn.0252-3116.2017.21.012
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