A Shilling Group Detection Framework Based on Deep Learning Techniques

Algorithm 2

Transition probability-based user neighbour sampling.

	Input: rating dataset
	sampling number K
	Output: sampling result SN
	Begin:
(1)
(2)	for each do
(3)
(4)	for each DO
(5)	calculate according to equations (1)–(8)
(6)	if  then
(7)
(8)	end if
(9)	end for
(10)	end for
(11)	for each do
(12)	sort according to transition probability in descending order
(13)	while do
(14)	//|| is an operation that joints two sets together.
(15)	end while
(16)	sample the first K users in and obtain sampling neighbour set
(17)
(18)	end for
(19)	return SN
	End