LATEX排版记录

\begin{itemize}
\item {} ...
\item {} ...
\item {}...
\item {} ...
\end{itemize}

\indent The main contributions of this paper are as follows:%主要贡献


\begin{itemize} 
\item {} To the best of our knowledge, we are the first to design the incentive mechanism, which stimulates the strategic workers to reach the least confidence for truth discovery in the crowdsourcing.
\item {} We propose a truth discovery algorithm as a component of the incentive mechanism for the crowdsourcing with copiers. Our truth discovery algorithm considers both the dependence and accuracy of workers. Further, we extend our truth discovery algorithm to the general cases, where the distribution of false values is nonuniform. 
\item {} We model the \textit{\underline{S}ocial \underline{O}ptimization \underline{A}ccuracy \underline{C}overage} (\textit{SOAC}) problem, and design a reverse auction mechanism to solve the \textit{SOAC} problem.  We show that the designed mechanism satisfies the desirable properties of computational efficiency, individual rationality, truthfulness, and guaranteed approximation.
\item {} To support the textual answers of crowdsourcing tasks, we propose \textit{S-DATE} (\textit{\underline{S}emantic-oriented \underline{DATE}}), which uses language representation model and clustering method to obtain the values of textual answers.
\end{itemize}

\begin{equation}
...
\end{equation}

\begin{equation}
	u_i  = p_i  - c_i
\end{equation}

\usepackage{algorithm}

\usepackage{algorithmic}

\begin{algorithm}  %算法2 Reverse Auction
	\caption{\textbf{: Reverse Auction}}
	\leftline{\textbf{Input:} {task set $T$}, {bid profile $B$}, {worker set $W$},{ accuracy}}
	\leftline{{requirement profile $\Theta$}, {accuracy matrix \textbf{A}}}
	\leftline{\textbf{Output:} {winner set $S$, payment \textbf{p}}}
	
	\leftline{ //Winner Selection Phase}
	\begin{algorithmic}[1]
		\State{$S \leftarrow \emptyset ,\Theta ‘ \leftarrow \Theta$};
		\While {$\sum\nolimits_{t_j  \in T} {\Theta ^j{‘}}  \ne 0$}
			\State{$i \leftarrow \arg \min _{k \in W\backslash S} \frac{{b_k }}{{\sum\nolimits_{t_j  \in T_k } {\min \{ \Theta ^j {‘},A_k^j \} } }}$};
			\State{$S \leftarrow S \cup \{ i\}$};
			\For {each $t_j  \in T_i $}
				\State{$\Theta ^j{‘} \leftarrow \Theta ^j {‘} - \min \{ \Theta ^j{‘},A_i^j \}$};
			\EndFor
		\EndWhile	

	\leftline{ //Payment Determination Phase}	
	\For {each $i \in W$}
		\State {$p_i  \leftarrow 0$};
	\EndFor
	\For {each $i \in S$}
		\State {$W‘ \leftarrow W\backslash \{ i\} ,S‘ \leftarrow \emptyset ,\Theta ‘‘ \leftarrow \Theta$};
		\While {$\sum\nolimits_{t_j  \in T} {\Theta ^j {‘‘}} \ne 0$}
			\State {$i_k  \leftarrow \arg \min _{k \in W‘\backslash S‘} \frac{{b_k }}{{\sum\nolimits_{t_j  \in T_k } {\min \{ \Theta ^j{‘‘},A_k^j \} } }}$};
			\State {$S‘ \leftarrow S‘ \cup \{ i_k \}$};
			\State {$p_i  \leftarrow \max \{ p_i ,\frac{{\sum\nolimits_{t_j  \in T_i } {\min \{ \Theta ^j{‘‘},A_i^j \} } }}{{\sum\nolimits_{t_j  \in T_{i_{_k } } } {\min \{ \Theta ^j {‘‘},A_{i_k }^j \} } }}b_{i_k } \}$};
			\For {each $t_j  \in T_{i_k }$}
				\State{$\Theta ^j{‘‘} \leftarrow \Theta ^j{‘‘} - \min \{ \Theta ^j{‘‘},A_{i_k }^j \}$}
			\EndFor
		\EndWhile
	\EndFor

	\end{algorithmic}
\end{algorithm}

\begin{figure} % 图16  Truthfulness of IMC2
	%\setlength{\abovecaptionskip}{-0.1cm}
	%\vspace{-0.5cm}
	\centering
	\subfigure[Utility of worker with ID=16 (winner)]{
		\begin{minipage}[t]{0.47\linewidth} %0.5\textwidth两图之间的距离
			\centering
			\includegraphics[width=1\linewidth]{pic_eps/utility_bid.eps} %图片大小
			%\caption{}
		\end{minipage}
	}
	\subfigure[Utility of worker with ID=74 (loser)]{
		\begin{minipage}[t]{0.47\linewidth}
			\centering
			\includegraphics[width=1\linewidth]{pic_eps/utility_bid_false.eps}
			%\caption{}
		\end{minipage}
	}
	\centering
	\caption{Truthfulness of \textit{IM$C^2$}}
\end{figure}

\begin{figure}[h] %图4 Transformer encoder architecture
	\centering  %插入的图片居中表示
	\includegraphics[width=0.7\linewidth]{pic_eps/Transformer.eps}  %插入的图，包括JPG,PNG,PDF,EPS等，放在源文件目录下
	\caption{\textit{Transformer} encoder architecture }  %图片的名称
	\label{fig:mcmthesis-logo}   %标签，用作引用
\end{figure}

\begin{table} %表1 copy的例子
  \caption{An example of conflicting values provided by crowdsourcing workers with copiers}
  \label{tab:freq}
  
  \linespread{1}
   \begin{tabular}{c|p{20pt}|p{25pt}|p{20pt}|p{20pt}|p{20pt}} %p{75pt}第一列
   %\begin{tabular}{cccccc}
    \toprule
     \diagbox {\textbf{Tasks}}{\textbf{Workers}}& {\textbf{1}}& {\textbf{2}}& {\textbf{3}}& {\textbf{4}} & {\textbf{5}}\    \midrule
	{\itshape   Stonebraker}& MIT& Berkeley & MIT & MIT & MS \	{\itshape   Dewitt}& MSR& MSR & UWise & UWisc & UWisc \	{\itshape   Bernstein}& MSR& MSR & MSR & MSR & MSR \	{\itshape   Carey}& UCI& AT\&T & BEA & BEA & BEA \	{\itshape   Halevy}& Google& Google & UW & UW & UW \  \bottomrule
\end{tabular}
\end{table}

\begin{table} %表2 常见符号解释
	\caption{Frequently used notations}
	\label{Symbol}
	{\begin{tabular}{p{50 pt}p{180 pt}}	
			\toprule
			\textbf{Symbol} & \textbf{Description} \			
			\midrule
			$W,n$ & {worker set, number of workers} \			$T,m$ & {task set, number of tasks} 			\bottomrule
			
	\end{tabular}}
\end{table}