# Welcome to Salmon’s documentation!

Salmon is a tool to easily allow collection of “triplet queries.” These queries are relative similarity judgments of the form “is object $$a$$ or $$b$$ closer to object $$h$$?” An example is shown below with facial similarities:

These queries provide a relative similarity measure: a response indicates that object $$a$$ is closer to object $$b$$ than object $$c$$ as determined by humans. For example, these triplet queries have been used by psychologists to determine what facial emotions human find similar:

Only distance is relevant in this embedding, not the vertical/horizontal axes. However, if you look closely, you can see two axes: positivity and intensity.

Salmon provides efficient methods for collecting these triplet queries. Typically, generating the embeddings above requires far too many human responses. Salmon provides the ability to generate the same embeddings with fewer human responses – in our experiments, about 1,000 queries are required to reach a particular quality level instead of about 3,000 queries. If you’re paying for each human response (say on Mechanical Turk), this means that collecting responses will be reduced by a factor of 3 when compared with naive methods of collecting triplet queries.

# Users

Salmon is currently being actively used by pyschologists from the University of Wisconsin–Madison, and has seen some user from pyschologists at the Louisiana State University and Canada’s Western University.

Algorithm Developers

## Other sources

This documentation is available at these locations:

Please file an issue if you can not access the documentation above.