Patent ID: 8402369

Claim:
A method for summarizing multiple documents, comprising: a. generating a model BUV T of the documents as a mixture of document clusters, each document in turn having a mixture of sentences, wherein U is a corresponding sentence-topic matrix, V is a corresponding document-topic matrix, and B is a corresponding term-sentence matrix; b. simultaneously representing summarization information and document cluster structure in the model BUV T ; c. determining a loss function l, where the loss function comprises l ( U,V )= KL ( A∥BUV T )− In Pr ( U,V ), where KL is the Kullback-Leibler divergence, and where A is a corresponding term-document matrix; d. evaluating and optimizing the model by translating a summarization and clustering problem into minimizing the loss l between the given documents and model reconstructed terms using the maximum likelihood estimation task comprising U , V = arg ⁢ ⁢ min ⁢ ⁢ U , V ⁢ l ⁡ ( U , V ) ; e. generating a summary of the documents at the same time as clustering documents into a given size of targeted summarization based on the model BUV T and the maximum likelihood estimation task.