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Which similarity measure evaluates relatedness by calculating the cosine of the angle between two vector representations of text?

easy📝 Conceptual Q2 of 15
NLP - Text Similarity and Search
Which similarity measure evaluates relatedness by calculating the cosine of the angle between two vector representations of text?
AManhattan distance
BEuclidean distance
CJaccard index
DCosine similarity
Step-by-Step Solution
Solution:

  1. Step 1: Identify similarity measures

    Cosine similarity measures the cosine of the angle between two vectors, indicating orientation similarity.

  2. Step 2: Compare with other measures

    Euclidean and Manhattan distances measure absolute distances, not angles; Jaccard index measures set overlap.

  3. Final Answer:

    Cosine similarity -> Option D

  4. Quick Check:

    Cosine similarity uniquely uses angle cosine to assess vector similarity. [OK]
Quick Trick: Cosine similarity uses angle cosine between vectors [OK]
Common Mistakes:
MISTAKES
  • Confusing cosine similarity with Euclidean distance
  • Thinking Jaccard index measures angles
  • Assuming Manhattan distance uses angles

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