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Hands-On Recommendation Systems with Python

You're reading from   Hands-On Recommendation Systems with Python Start building powerful and personalized, recommendation engines with Python

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Product type Paperback
Published in Jul 2018
Publisher Packt
ISBN-13 9781788993753
Length 146 pages
Edition 1st Edition
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Author (1):
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Rounak Banik Rounak Banik
Author Profile Icon Rounak Banik
Rounak Banik
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Suggestions for improvements

The content-based recommenders we've built in this chapter are, of course, nowhere near the powerful models used in the industry. There is still plenty of scope for improvement. In this section, I will suggest a few ideas for upgrading the recommenders that you've already built:

  • Experiment with the number of keywords, genres, and cast: In the model that we built, we considered at most three keywords, genres, and actors for our movies. This was, however, an arbitrary decision. It is a good idea to experiment with the number of these features in order to be considered for the metadata soup.

  • Come up with more well-defined sub-genres: Our model only considered the first three keywords that appeared in the keywords list. There was, however, no justification for doing so. In fact, it is entirely possible that certain keywords appeared in only...

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