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Building Recommendation Engines by Suresh Kumar Gorakala

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Popular methodologies

In earlier chapters, we have seen various recommendation engines. In this section, we touch upon a few popular methodologies, which are actively been employed in building recommendation engines for improving the robustness and relevance of the recommendations, such as:

  • Serendipity
  • Temporal aspects
  • A/B testing
  • Feedback mechanism

Serendipity

One of the drawbacks of recommendation engines is that the recommendation engine will push us to a corner where the items to be suggested or discovered will be entirely based on what we have looked for in the past or what we are currently looking for:

Serendipity

Credits: neighwhentheyrun

They work just the ...

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