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In conducting DIA, using precedents is both expedient and also leads to more fairness and unity in the application of standards, as applying those precedents in new contexts can reveal fresh information and nuances or invalid assumptions in those precedents, and can thus lead to revision and fine-tuning of these precedents, with the improvements applying equally to all (even retroactively, via backpropagation). Therefore, it would be useful to be able to identify relevant precedents when appraising a new project to aid the DIA analyst.
For this purpose, we could create a dataset of projects together with metadata such as the ideas in their idea tree. Then, construct a structured database from this dataset (for instance, a graph database using something like Neo4j, with project nodes connected to idea nodes), and then provide a recommendation facility that allows us to find related projects. It could use a simple collaborative filtering algorithm, e.g. "for this project, given the ideas it entails, what other projects are the most similar in terms of exhibiting those ideas?"
The text was updated successfully, but these errors were encountered:
In conducting DIA, using precedents is both expedient and also leads to more fairness and unity in the application of standards, as applying those precedents in new contexts can reveal fresh information and nuances or invalid assumptions in those precedents, and can thus lead to revision and fine-tuning of these precedents, with the improvements applying equally to all (even retroactively, via backpropagation). Therefore, it would be useful to be able to identify relevant precedents when appraising a new project to aid the DIA analyst.
For this purpose, we could create a dataset of projects together with metadata such as the ideas in their idea tree. Then, construct a structured database from this dataset (for instance, a graph database using something like Neo4j, with project nodes connected to idea nodes), and then provide a recommendation facility that allows us to find related projects. It could use a simple collaborative filtering algorithm, e.g. "for this project, given the ideas it entails, what other projects are the most similar in terms of exhibiting those ideas?"
The text was updated successfully, but these errors were encountered: