Hykilpikonna
88 lines
3.1 KiB
TeX
88 lines
3.1 KiB
TeX
\documentclass[11pt]{article}
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\usepackage{amsmath}
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\usepackage[utf8]{inputenc}
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\usepackage[margin=0.75in]{geometry}
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\title{CSC111 Assignment 3: Graphs, Recommender Systems, and Clustering}
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\author{Azalea Gui \& Peter Lin}
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\date{\today}
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\newcommand{\N}{\mathbb{N}}
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\newcommand{\Z}{\mathbb{Z}}
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\newcommand{\R}{\mathbb{R}}
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\newcommand{\cO}{\mathcal{O}}
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\newcommand{\floor}[1]{\left\lfloor #1 \right\rfloor}
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\newcommand{\code}[1]{\texttt{#1}}
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\begin{document}
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\maketitle
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\section*{Part 1: The book review graph and simple recommendations}
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\begin{enumerate}
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\item[1.]
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Complete this part in the provided \texttt{a3\_part1.py} starter file.
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Do \textbf{not} include your solution in this file.
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\item[2.]
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Running Time Analysis for \texttt{load\_review\_graph}:
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Let $n$ be the number of lines in \texttt{book\_names\_file}, let $m$ be the number of lines in \texttt{reviews\_file}.
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There are two operations that involves iteration in the function, one reads the book names file and creates the \texttt{mp} dictionary, and the other one reads the reviews file and adds vertices to the graph.
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In creating $mp$, the program first opened the file and created a \texttt{csv.reader}, which are both constant-time operations. Then, the dictionary comprehension statement loops through all $n$ lines, running only constant-time operations in each iteration for adding the book id and name pair into the dictionary, resulting in a running time of $\Theta(n)$. Summing up all the operations for creating $mp$ and ignoring constant-time operations, the running time would be $\in \Theta(n)$.
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For adding the vertices, it also opened the file and created a \texttt{csv.reader} in constant time. Then, the loop iterates through all $m$ lines. In each iteration, two vertices and one edge are added, and it also accessed $mp$ to retrieve the book name, which are all constant time operations. Therefore, the total running time would be contained by $\in \Theta(m)$.
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Since there are only constant-time operations outside the two iterating operations, the total running time of the function would be $\in \Theta(m + n)$
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\item[3.]
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Complete this part in the provided \texttt{a3\_part1.py} starter file.
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Do \textbf{not} include your solution in this file.
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\item[4.]
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Complete this part in the provided \texttt{a3\_part1.py} starter file.
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Do \textbf{not} include your solution in this file.
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\end{enumerate}
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\section*{Part 2: Weighted graphs, recommendations, review prediction}
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Complete this part in the provided \texttt{a3\_part2\_recommendations.py} and \texttt{a3\_part2\_predictions.py} starter files.
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Do \textbf{not} include your solution in this file.
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\newpage
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\section*{Part 3: Finding book clusters}
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\begin{enumerate}
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\item[1.]
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Complete this part in the provided \texttt{a3\_part3.py} starter file.
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Do \textbf{not} include your solution in this file.
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\item[2.]
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Complete this part in the provided \texttt{a3\_part3.py} starter file.
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Do \textbf{not} include your solution in this file.
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\item[3.]
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\begin{enumerate}
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\item[(a)]
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TODO: Write your answer here.
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\item[(b)]
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TODO: Write your answer here.
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\item[(c)]
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TODO: Write your answer here.
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\item[(d)]
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\emph{Not to be handed in.}
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\end{enumerate}
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\end{enumerate}
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\end{document}
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