Systems and methods for capture of relationships within information

A non-transitory computer readable medium, the nontransitive computer readable medium comprising processing instructions executable by a processor to perform a method, the method comprising:

• receiving a multidimensional dataset, each data point in the multidimensional dataset having multiple dimensions;
• receiving a set of landmarks from the data points, the set of landmarks being a subset of the multidimensional dataset;
• mapping each of the set of landmarks into a finite metric space based on values of the dimensions of each landmark;
• computing, for each landmark, a plurality of nearest neighbor landmarks in the set of landmarks, distance between every two landmarks being based on dimensions of each of the two landmarks and the finite metric space;
• identifying at least one pair of landmarks that are nearest neighbors to each other relative to the other pairs of landmarks;
• adding an edge between the at least one pair of landmarks;
• and
• for each data point in the multidimensional dataset that is not a member of the set of landmarks:
• determining distances of each of the data points that is not the member of the set of landmarks to the finite metric space to at least one of the landmarks points, and
• projecting each data point that is not a member of the set of landmarks to the finite metric space based on the determined distances thereby enabling at least one shape to indicate relationships in the data.

A non-transitory computer readable medium, the nontransitive computer readable medium comprising processing instructions executable by a processor to perform a method, the method comprising:

• receiving a multidimensional dataset, each data point in the multidimensional dataset having multiple dimensions;
• receiving a set of landmarks from the data points, the set of landmarks being a subset of the multidimensional dataset;
• mapping each of the set of landmarks into a finite metric space based on values of the dimensions of each landmark;
• computing, for each landmark, a plurality of nearest neighbor landmarks in the set of landmarks, distance between every two landmarks being based on dimensions of each of the two landmarks and the finite metric space;
• identifying at least one pair of landmarks that are nearest neighbors to each other relative to the other pairs of landmarks;
• adding an edge between the at least one pair of landmarks;
• and
• for each data point in the multidimensional dataset that is not a member of the set of landmarks:
• determining distances of each of the data points that is not the member of the set of landmarks to the finite metric space to at least one of the landmarks points, and
• projecting each data point that is not a member of the set of landmarks to the finite metric space based on the determined distances thereby enabling at least one shape to indicate relationships in the data.