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A New Method of Social Information Recommendation by Combining Contextual Factors
Received date: 2015-06-09
Revised date: 2015-09-07
Online published: 2015-11-20
[Purpose/significance] Since the current information recommendation method integrating contextual factors leads to the loss of information valuedue to excessive filtration. This papercompletes multidimensional recommendation based on use-resource-context.[Method/process] For such problems, this paper integrated context factors into the recommending process, and completed users'interest miningunder different contexts. Firstly, an initial interest value was given using the index of socialnetworks. Then the weight for users' interest was proposed from the perspective ofspatial distance. Finally, users' interest score prediction was implemented according tocollaborative recommendation, and the interest recommendations for the users was completed. [Result/conclusion] The comparison between the two-dimensional recommendation and the multidimensional recommendation shows that the recommendation integrating context factors can more accurately reveal the users' interest and improve the quality of recommendation, and provide a reference for social media recommendation service.
Fang Xiaoke . A New Method of Social Information Recommendation by Combining Contextual Factors[J]. Library and Information Service, 2015 , 59(22) : 105 -111,129 . DOI: 10.13266/j.issn.0252-3116.2015.22.016
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