Patent Document ID: 7912868
Application ID: 11126184

Base Claim:
1. A machine-readable non-transitory medium having instructions stored thereon, where the instructions, when read by the machine, cause the machine to perform the steps of: accessing a semantic representation associated with a first dataset and a semantic representation associated with a second dataset, wherein at least one of the semantic representation associated with the first dataset and the semantic representation associated with the second dataset is a trainable semantic vector generated based on at least one data point included in a respective dataset and known relationships between predetermined data points and predetermined categories to which the predetermined data points may relate; determining a similarity between the semantic representation associated with the first dataset and the semantic representation associated with the second dataset; and selectively relating the first dataset to the second dataset based on a result of the determining step; wherein each attribute in a trainable semantic vector indicates how likely a dataset represented by the trainable semantic vector belongs to one of the predetermined categories, and the trainable semantic vector has a dimension equal to the number of the predetermined categories.

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Claim 10:
10. The machine-readable medium of claim 1 , wherein the trainable semantic vector associated with the respective dataset is generated further based on information related to at least one user or at least one dataset linked to said dataset.