Tokenize the dataset and convert the data into a document feature matrix Calculate cosine similarity across documents and plot the output
By the end of this project, you will learn about the concept of document similarity in textual analysis in R. You will know how to load and pre-process a data set of text documents by converting the data set into a corpus and document feature matrix. You will know how to calculate the cosine similarity between documents and explore and plot the output of your calculation.
cosine similarity
Text Analysis
Document Similarity
Data Visualization (DataViz)
Text Corpus
In a video that plays in a split-screen with your work area, your instructor will walk you through these steps:
Load textual data into R and turn it into a corpus object and understand the concept of calculating document similarity in textual analysis
Extract meta-data from text document filenames and subset the data frame to exclude unwanted data
Tokenize and clean the dataset and convert the data into a document feature matrix
Calculate cosine similarity across documents and plot the output
Your workspace is a cloud desktop right in your browser, no download required
In a split-screen video, your instructor guides you step-by-step
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Yes, everything you need to complete your Guided Project will be available in a cloud desktop that is available in your browser.
You'll learn by doing through completing tasks in a split-screen environment directly in your browser. On the left side of the screen, you'll complete the task in your workspace. On the right side of the screen, you'll watch an instructor walk you through the project, step-by-step.
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