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{{Main|Technical overview of the ratings system}} |
{{Main|Technical overview of the ratings system}} |
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[[Opinion aggregation|Aggregation]] refers to the way we combine the [[Opinion|opinions]] of others to obtain a final value of the opinion. A [[Polling|poll]] which takes the sum of each person's candidate preference in an [[Election|election]] and then calculates the percentage for each candidate is an aggregation technique. |
[[Opinion aggregation|Aggregation]] refers to the way we combine the [[Opinion|opinions]] of others to obtain a final value of the [[opinion]]. A [[Polling|poll]] which takes the sum of each person's candidate preference in an [[Election|election]] and then calculates the percentage for each candidate is an aggregation technique. |
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A number of aggregation techniques are possible: |
A number of aggregation techniques are possible: |
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# [[Binned and continuous distributions|Binned and continuous distributions]] |
# [[Binned and continuous distributions|Binned and continuous distributions]] |
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# [[Population distributions and graphical output with privacy|Population distributions and graphical output with privacy]] |
# [[Population distributions and graphical output with privacy|Population distributions and graphical output with privacy]] |
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[[Privacy in ratings aggregation|Privacy]] is an important issue in ratings aggregation and each algorithm will require customized treatment to deal with it. |
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More algorithms will be developed over time. Furthermore, the software will be built with an API to allow users to add their own algorithms. |
More algorithms will be developed over time. Furthermore, the software will be built with an API to allow users to add their own algorithms. |
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Revision as of 18:04, 11 September 2024
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:
- Bayes' equation with a simple example of its use.
- Simple averaging, a privacy enhancing variant thereof, and an averaging technique using with continuous input distributions, complex trust, and intermediate results.
- Trust weighted averaging
- An analysis of these methods and simple weighted averaging
- Trust-weighted histograms
- Trust/Probability/Population graphs algorithm
- Binned and continuous distributions
- 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.