Cosine¶
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class
py_stringmatching.similarity_measure.cosine.
Cosine
[source]¶ Computes a variant of cosine measure known as Ochiai coefficient.
This is not the cosine measure that computes the cosine of the angle between two given vectors. Rather, it computes a variant of cosine measure known as Ochiai coefficient (see the Wikipedia page “Cosine Similarity”). Specifically, for two sets X and Y, this measure computes:
\(cosine(X, Y) = \frac{|X \cap Y|}{\sqrt{|X| \cdot |Y|}}\)Note
- In the case where one of X and Y is an empty set and the other is a non-empty set, we define their cosine score to be 0.
- In the case where both X and Y are empty sets, we define their cosine score to be 1.
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get_raw_score
(set1, set2)[source]¶ Computes the raw cosine score between two sets.
Parameters: set1,set2 (set or list) – Input sets (or lists). Input lists are converted to sets. Returns: Cosine similarity (float) Raises: TypeError
– If the inputs are not sets (or lists) or if one of the inputs is None.Examples
>>> cos = Cosine() >>> cos.get_raw_score(['data', 'science'], ['data']) 0.7071067811865475 >>> cos.get_raw_score(['data', 'data', 'science'], ['data', 'management']) 0.4999999999999999 >>> cos.get_raw_score([], ['data']) 0.0
References
- String similarity joins: An Experimental Evaluation (a paper appearing in the VLDB 2014 Conference).
- Project Flamingo at http://flamingo.ics.uci.edu.
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get_sim_score
(set1, set2)[source]¶ Computes the normalized cosine similarity between two sets.
Parameters: set1,set2 (set or list) – Input sets (or lists). Input lists are converted to sets. Returns: Normalized cosine similarity (float) Raises: TypeError
– If the inputs are not sets (or lists) or if one of the inputs is None.Examples
>>> cos = Cosine() >>> cos.get_sim_score(['data', 'science'], ['data']) 0.7071067811865475 >>> cos.get_sim_score(['data', 'data', 'science'], ['data', 'management']) 0.4999999999999999 >>> cos.get_sim_score([], ['data']) 0.0