Similarity Measure
(Redirected from Distance Functions)
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A similarity measure is a distance measure of a similarity relationship.
- AKA: Affinity Measure, Relatedness Function.
- Context:
- range: Similarity Score.
- It can (often) be based on a Distance Function.
- It can range from being a Symmetric Similarity Measure to being a Non-Symmetric Similarity Measure (like KL).
- It can range from being a Syntactic Similarity Measure to being a Semantic Similarity Measure.
- It can be computed by a Similarity Measure Computation Operation.
- It can range from being a Set Similarity, a Multiset Similarity, a Multiset Pattern Similarity, a Tuple-Space Similarity, a Metric-Space Similarity, a Graph-based Similarity, ...
- It can be a Domain-Specific Similarity Measure, such as a Word Semantic Similarity Measure lexical items similarity measure.
- It can be a Similarity Metric.
- Example(s):
- Counter-Example(s):
- See: Similarity Matrix, Clustering Task, Local Search; Equivalence Relationship.
References
- http://scholar.google.com/scholar?q=%22a+Similarity+Measure%22
- http://scholar.google.com/scholar?q=%22similarity+measure+such+as%22