Patent Document ID: 8825648
Application ID: 12760844

Base Claim:
1. A method comprising: under a control of one or more processors, identifying multiple concept-units from a multi-language document corpus, a respective concept-unit including a set of documents in a plurality of languages describing a particular concept, the identifying including identifying one or more hyperlinks or references within a respective document that identify one or more other documents in one or more other languages relating to the particular concept; and modeling the concept-units of the multi-language document corpus by maintaining a separation of term-by-document matrices for the plurality of languages to create a generative model, the generative model representing: a plurality of universal topics, at least one respective universal topic being defined by a plurality of topic word distributions in the plurality of languages, at least one of the plurality of topic word distributions for a respective universal topic corresponding to a respective language from the plurality of languages and including one or more words in the respective language with corresponding probability values characterizing the respective universal topic; and a topic distribution for at least one concept-unit, the topic distribution for a respective concept-unit including one or more universal topics and their distributions for the respective concept-unit, the set of documents in the different plurality of languages of the respective concept-unit being constrained to share a common topic distribution.

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Claim 7:
7. A method as recited in claim 1 , further comprising: obtaining topic distributions of documents of a classified document corpus; obtaining topic distributions of documents of an unclassified document corpus; comparing topic distributions between the documents of the unclassified document corpus and the documents of the classified document corpus; and classifying one or more documents of the unclassified document corpus according to classifications of documents in the classified document corpus having common topic distributions with the one or more documents of the unclassified document corpus.