An Adaptive Technique for Weighting Multiple Factors in Followee Recommendation Algorithms


The accurate suggestion of interesting friends arises as a crucial issue in recommendation systems. This work argues that the criteria for recommending friends (or followees) needs to be adapted and combined according to each user's preferences. A technique is proposed for adapting such criteria to the characteristics of previously selected followees. Experimental evaluation showed that the technique improved the precision of static weighting strategies. Results highlighted the importance of adapting to changes in user preferences over time.

CPCR+ITWP'15:, pp. 32–33