4. A cross-lingual information retrieval system comprising: a monolingual information retrieval system configured to retrieve documents from a corpus of documents in a target natural language based on a received query in the target natural language; and a processor configured to add cross-lingual information retrieval capability to the monolingual information retrieval system, the processor performing a process including: representing a starting query in a source natural language by a starting query language model in the source natural language having zero values for words not in the starting query, translating the starting query in the source natural language into the target natural language and inputting the translated starting query to the monolingual information retrieval system to retrieve a set of pseudo-feedback documents in the target natural language, generating a source language-to-target language translation model based on the set of pseudo-feedback documents in the target natural language and the starting query language model, and re-translating the starting query from the source natural language into the target natural language using the translation model and inputting the re-translated starting query to the monolingual information retrieval system to retrieve an updated set of documents in the target natural language; wherein the translation model is generated by maximizing a likelihood of the set of pseudo-feedback documents in the target natural language given the starting query language model in the source natural language using an expectation maximization (EM) algorithm with the translated starting query as the starting translation model.
4. A cross-lingual information retrieval system comprising: a monolingual information retrieval system configured to retrieve documents from a corpus of documents in a target natural language based on a received query in the target natural language; and a processor configured to add cross-lingual information retrieval capability to the monolingual information retrieval system, the processor performing a process including: representing a starting query in a source natural language by a starting query language model in the source natural language having zero values for words not in the starting query, translating the starting query in the source natural language into the target natural language and inputting the translated starting query to the monolingual information retrieval system to retrieve a set of pseudo-feedback documents in the target natural language, generating a source language-to-target language translation model based on the set of pseudo-feedback documents in the target natural language and the starting query language model, and re-translating the starting query from the source natural language into the target natural language using the translation model and inputting the re-translated starting query to the monolingual information retrieval system to retrieve an updated set of documents in the target natural language; wherein the translation model is generated by maximizing a likelihood of the set of pseudo-feedback documents in the target natural language given the starting query language model in the source natural language using an expectation maximization (EM) algorithm with the translated starting query as the starting translation model. 7. The cross-lingual information retrieval system as set forth in claim 4 , further comprising: a machine translation engine configured to translate the updated set of documents from the target natural language to the source natural language; and an output device configured to represent the machine-translated updated set of documents in a human-perceptible representation.