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Aggregation techniques

From Information Rating System Wiki
Revision as of 18:04, 11 September 2024 by Pete (talk | contribs)

Main article: Technical overview of the ratings system

Aggregation refers to the way we combine the opinions of others to obtain a final value of the opinion. A poll which takes the sum of each person's candidate preference in an election and then calculates the percentage for each candidate is an aggregation technique.

A number of aggregation techniques are possible:

  1. Bayes' equation with a simple example of its use.
  2. Simple averaging, a privacy enhancing variant thereof, and an averaging technique using with continuous input distributions, complex trust, and intermediate results.
  3. Trust weighted averaging
  4. An analysis of these methods and simple weighted averaging
  5. Trust-weighted histograms
  6. Trust/Probability/Population graphs algorithm
  7. Binned and continuous distributions
  8. Population distributions and graphical output with privacy

Privacy is an important issue in ratings aggregation and each algorithm will require customized treatment to deal with it.

More algorithms will be developed over time. Furthermore, the software will be built with an API to allow users to add their own algorithms.