1. A method performed by a data processing apparatus, the method comprising: selecting, by the data processing apparatus, object representations from a dataset storing a plurality of object representations, each object representation being an association of: an object identifier that identifies an object instance in a dataset and corresponds to an object; a context value that identifies a context of the object; and a set of feature values that identify features of the object; wherein each object identifier is unique in the dataset, and each context value is associated with one or more object identifiers; for each feature value: determining an inter-context score that is proportional to the number of different context values in the dataset that are associated with the feature value, wherein the inter-context score is a probability that a random pair of object representations that each include a particular feature value are each associated with different context values and is determined independent of inter-context scores of other feature values; and determining an intra-context score that is proportional to the number of times the feature value is associated with each context value, wherein the intra-context score is a probability that a random pair of object representations that each include the particular feature value are each associated with the same context value and is determined independent of intra-context scores of other feature values; and for a selected pair of object representations, determining a similarity score based on inter-context scores and intra-context scores of matching feature values in the set of features for the pair of object representations, the similarity score being a measure of the similarity of the object representations in the pair of object representations, the determining comprising generating a respective set of feature weights for the set of features of the selected pair of object representations, each feature weight in the respective set of feature weights corresponding to a respective feature and being determined from the inter-context score and intra-context score for the respective feature and further determined independent of the inter-context score and intra-context score for other respective features.
1. A method performed by a data processing apparatus, the method comprising: selecting, by the data processing apparatus, object representations from a dataset storing a plurality of object representations, each object representation being an association of: an object identifier that identifies an object instance in a dataset and corresponds to an object; a context value that identifies a context of the object; and a set of feature values that identify features of the object; wherein each object identifier is unique in the dataset, and each context value is associated with one or more object identifiers; for each feature value: determining an inter-context score that is proportional to the number of different context values in the dataset that are associated with the feature value, wherein the inter-context score is a probability that a random pair of object representations that each include a particular feature value are each associated with different context values and is determined independent of inter-context scores of other feature values; and determining an intra-context score that is proportional to the number of times the feature value is associated with each context value, wherein the intra-context score is a probability that a random pair of object representations that each include the particular feature value are each associated with the same context value and is determined independent of intra-context scores of other feature values; and for a selected pair of object representations, determining a similarity score based on inter-context scores and intra-context scores of matching feature values in the set of features for the pair of object representations, the similarity score being a measure of the similarity of the object representations in the pair of object representations, the determining comprising generating a respective set of feature weights for the set of features of the selected pair of object representations, each feature weight in the respective set of feature weights corresponding to a respective feature and being determined from the inter-context score and intra-context score for the respective feature and further determined independent of the inter-context score and intra-context score for other respective features. 4. The method of claim 1 , further comprising: generating a context histogram for each feature value in the sets of feature values, the context histogram defining the number of times the feature value co-occurs with each context value in the dataset; and generating a feature weight for each feature value based on the context histogram of the feature value.