# Expectation maximization modeling

The setting of my problem is as follows: we have a set of questions $T_1,..T_n$ and a set of workers $W_1,W_2,...,W_m$ and a matrix where a cell $c[i,j]$ is the answer of question $T_i$ by worker $W_j$. The domain of answers for each question is finite and discrete. I want to calculate the trustworthiness of the workers (whether I should trust his/her answers) and the correctness of the answers (the probability that an answer is correct). How can I model and solve this problem using EM?

According to wikipedia, there are three components of an EM algorithm: a set $X$ of observed data, a set of unobserved latent data or missing values $Z$ , and a vector of unknown parameters $\theta$, along with a likelihood function $L(\theta;X,Z)=p(X,Z|\theta)$.

In my opinion, the observed data $X$ is obviously the answers. But I don't know what is $Z$ $\theta$ and $L$.