16. At least one device comprising: one or more processors; memory storing instructions, that when executed on the one or more processors, configure the at least one device to perform operations comprising: identifying multiple concept-units from a multi-language document corpus, a particular concept-unit of the multiple concept-units including a set of documents in different languages describing a particular concept; deriving a universal topic space from the multiple concept-units; identifying, based on the particular concept-unit and the universal topic space, a first topic distribution associated with the particular concept-unit, the first topic distribution comprising: (i) two or more topics of the universal topic space for which individual documents classified within the particular concept-unit are to contain; and (ii) one or more significance values, wherein individual significance values represent a significance of a corresponding universal topic of the two or more topics; and analyzing a new document to place it within the universal topic space, wherein the analyzing comprises: obtaining a second topic distribution of the new document, wherein the second topic distribution is based at least in part on the universal topic space; comparing the second topic distribution of the new document with the first topic distribution associated with the particular concept-unit; and classifying the new document within the universal topic space, based at least in part on the comparing.
16. At least one device comprising: one or more processors; memory storing instructions, that when executed on the one or more processors, configure the at least one device to perform operations comprising: identifying multiple concept-units from a multi-language document corpus, a particular concept-unit of the multiple concept-units including a set of documents in different languages describing a particular concept; deriving a universal topic space from the multiple concept-units; identifying, based on the particular concept-unit and the universal topic space, a first topic distribution associated with the particular concept-unit, the first topic distribution comprising: (i) two or more topics of the universal topic space for which individual documents classified within the particular concept-unit are to contain; and (ii) one or more significance values, wherein individual significance values represent a significance of a corresponding universal topic of the two or more topics; and analyzing a new document to place it within the universal topic space, wherein the analyzing comprises: obtaining a second topic distribution of the new document, wherein the second topic distribution is based at least in part on the universal topic space; comparing the second topic distribution of the new document with the first topic distribution associated with the particular concept-unit; and classifying the new document within the universal topic space, based at least in part on the comparing. 17. At least one device as recited in claim 16 , wherein deriving the universal topic space comprises inferring a plurality of universal topics from the multiple concept-units, each of the plurality of universal topics being defined by a plurality of topic word distributions corresponding respectively to the different languages.