[Retracted] Combining Latent Factor Model for Dynamic Recommendations in Community Question Answering Forums

Algorithm 2

Profile segmentation analysis.

	Input: A feature vector v from user latent profile lpu Output: Output matrix O representing similar users in similar groups
	Procedure of K-Means:
(1)	Determine the number of clusters K.
(2)	Perform the initial process of forming K-center clusters using .
(3)	Randomly assign any data point to the closest cluster. The distance is calculated as .
(4)	Reassign the datapoints to each cluster based on the distance between datapoint and center of each cluster as
	where aij represents the membership value of xi point to the center of cluster K, ci and d denotes the minimum distance between xi.
(5)	Recompute the cluster center to get the cluster with the minimum distance. An objective function is defined as .
(6)	If the iterations number is less than the maximum number of iterations, then repeat step 3; otherwise, return to the result of the clustering.