Table 1 Basic notations throughout this paper

WS= \(\{ w_{i} \}^{m}_{i=1}\)

WS is the set of workers, w _i is the i-th worker, m is the total number of workers

VS= \(\{ v_{j} \}^{n}_{j=1}\)

VS is the set of tasks, v _j is the j-th task, n is the total number of tasks

CS= \(\{ c_{k} \}^{o}_{k=1}\)

CS is the set of task categories, c _k is the k-th task category, o is the total number

of task categories

\(l \in \mathbb {R}\)

l is the number of dimensions of latent feature space

\(W \in \mathbb {R}^{l \times m}\)

W is the worker latent feature matrix

\(V \in \mathbb {R}^{l \times n}\)

V is the task latent feature matrix

\(C \in \mathbb {R}^{l \times o}\)

C is the task category latent feature matrix

R = {r _ij },

R is the worker-task preferring matrix, r _ij is the extent of the favor of task v _j

\(R \in \mathbb {R}^{m \times n}\)

for worker w _i

U = {u _ik },

U is the worker-category preferring matrix, u _ik is the extent of worker w _i ’s

\(U \in \mathbb {R}^{m \times o}\)

preference for category c _k

D = {d _jk },

D is the task-category grouping matrix, d _jk indicates the task category c _k that

\(D \in \mathbb {R}^{n \times o}\)

task v _j belongs to

(i,j)∈P S

PS is the set of indexes where the rating r _ij is unknown

N(x|μ,σ ²)

Probability density function of the Gaussian distribution with mean μ and variance σ ²