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Saved by uncleflo on December 23rd, 2018.
In the previous chapter, we explored in depth what we mean by the tidy text format and showed how this format can be used to approach questions about word frequency. This allowed us to analyze which words are used most frequently in documents and to compare documents, but now let’s investigate a different topic. Let’s address the topic of opinion mining or sentiment analysis. When human readers approach a text, we use our understanding of the emotional intent of words to infer whether a section of text is positive or negative, or perhaps characterized by some other more nuanced emotion like surprise or disgust. We can use the tools of text mining to approach the emotional content of text programmatically, as shown in Figure 2.1.
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Saved by uncleflo on March 21st, 2013.
This is meant to be a brief tutorial aimed at beginners who want to get a conceptual grasp on the database normalization process. I find it difficult to visualize these concepts using words alone, so I shall rely as much as possible upon pictures and diagrams. To demonstrate the main principles involved, we will take the classic example of an Invoice and level it to the Third Normal Form. We will also construct an Entity Relationship Diagram (ERD) of the database as we go.
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