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Upload app.py
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app.py
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@@ -88,7 +88,7 @@ Similarly, when you input a set of tags, the system creates a pseudo-document fo
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It then compares your tags against each artist's collection, essentially finding which artist's tags are most "similar" to yours.
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This method helps identify artists whose work is closely aligned with the themes or elements you're interested in.
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For those curious about the underlying mechanics of comparing text-like data, we employ the TF-IDF (Term Frequency-Inverse Document Frequency) method, a standard approach in information retrieval, and reduce the TF-IDF matrix to a reasonable size using Singular Value Decomposition.
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You can read more about TF-IDF on its [Wikipedia page](https://en.wikipedia.org/wiki/Tf%E2%80%93idf) and Singular Value Decomposition on its [Wikipedia page]
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## How does the tag corrector work?
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It then compares your tags against each artist's collection, essentially finding which artist's tags are most "similar" to yours.
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This method helps identify artists whose work is closely aligned with the themes or elements you're interested in.
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For those curious about the underlying mechanics of comparing text-like data, we employ the TF-IDF (Term Frequency-Inverse Document Frequency) method, a standard approach in information retrieval, and reduce the TF-IDF matrix to a reasonable size using Singular Value Decomposition.
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You can read more about TF-IDF on its [Wikipedia page](https://en.wikipedia.org/wiki/Tf%E2%80%93idf) and Singular Value Decomposition on its [Wikipedia page](https://en.wikipedia.org/wiki/Singular_value_decomposition).
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## How does the tag corrector work?
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