A method using distributed representations of data items within a first corpus of data documents clustered in a first two-dimensional metric space to generate a cluster of distributed representations in a second two-dimensional metric space, the method comprising: clustering in a two-dimensional metric space, by a reference map generator, executing on a computing device, a set of data documents of the first corpus of data documents selected according to at least one criterion, generating a semantic map; associating, by the semantic map, a coordinate pair with each of the set of data documents; generating, by a parser executing on the computing device, an enumeration of data items occurring in the set of data documents; determining, by a representation generator executing on the computing device, for each data item in the enumeration, occurrence information including: (i) a number of data documents in which the data item occurs, (ii) a number of occurrences of the data item in each data document, and (iii) the coordinate pair associated with each data document in which the data item occurs; generating, by the representation generator, a distributed representation for each data item using the occurrence information; receiving, by a sparsifying module executing on the computing device, an identification of a maximum level of sparsity; reducing, by the sparsifying module, a total number of set bits within each distributed representation based on the maximum level of sparsity to generate a sparse distributed representation (SDR) having a normative fillgrade; storing each of the SDRs in an SDR database; extracting snippets from a second corpus of data documents; identifying which of those snippets is already associated with an SDR in the SDR database; and clustering in a second two-dimensional metric space, by the reference map generator, executing on the computing device, a set of SDRs retrieved from the SDR database and associated with the identified snippets, generating a second semantic map for the second corpus of data documents. clustering in a two-dimensional metric space, by a reference map generator, executing on a computing device, a set of data documents of the first corpus of data documents selected according to at least one criterion, generating a semantic map; associating, by the semantic map, a coordinate pair with each of the set of data documents; generating, by a parser executing on the computing device, an enumeration of data items occurring in the set of data documents; determining, by a representation generator executing on the computing device, for each data item in the enumeration, occurrence information including: (i) a number of data documents in which the data item occurs, (ii) a number of occurrences of the data item in each data document, and (iii) the coordinate pair associated with each data document in which the data item occurs; generating, by the representation generator, a distributed representation for each data item using the occurrence information; receiving, by a sparsifying module executing on the computing device, an identification of a maximum level of sparsity; reducing, by the sparsifying module, a total number of set bits within each distributed representation based on the maximum level of sparsity to generate a sparse distributed representation (SDR) having a normative fillgrade; storing each of the SDRs in an SDR database; extracting snippets from a second corpus of data documents; identifying which of those snippets is already associated with an SDR in the SDR database; and clustering in a second two-dimensional metric space, by the reference map generator, executing on the computing device, a set of SDRs retrieved from the SDR database and associated with the identified snippets, generating a second semantic map for the second corpus of data documents. <EOS>