8. The method of claim 7 , further comprising smoothing the inter-context scores and intra-context scores by a first value p and a second value m so that determining the inter-context score is based on a summing over each context value in the dataset values equal to: 
 (( nc,f+p*m )*( nf−nc,f+p*m ))/(( nf+m )*( nf− 1 +m )); and determining the intra-context score based on a summing over each context value in the dataset values equal to: 
 (( nc,f+p*m )*( nf− 1 +p*m ))/(( nf+m )*( nf− 1 +m )).
7. 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: a 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; and determining an intra-context score that is proportional to the number of times the feature value is associated with each context value; and for a selected pair of object representations, determining a similarity score based on an inter-context score and an intra-context score of a matching feature value 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, 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 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 wherein determining the inter-context score and intra-context score comprises for each feature value in the sets of features in the dataset comprises: determining a number of object representations in the dataset that include the feature value; for each context value in the dataset, determining a number nc of object representations including the context value; for each context value in the dataset, determining a number nc,f of object representations including the context value and including the feature value; determining the inter-context score based on a summing over each context value in the dataset values proportional to: 
 ( nc,f *( nf−nc,f ))/( nf *( nf− 1)); and determining the intra-context score based on a summing over each context value in the dataset values proportional to: 
 ( nc,f *( nf− 1))/( nf *( nf− 1)).