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eQuery is a Natural Language Processing-based automatic information access system which implements algorithms that interpret language at all the levels at which humans are known to extract meaning. These are the morphological, lexical, syntactic, semantic, discourse and pragmatic levels. Using these levels eQuery extracts important concepts and relations from texts (both documents and queries) by applying sophisticated and proven natural language processing techniques.
The information retrieval capabilities exist in a 2-stage retrieval system, in which the Language-to-Logic (L-2-L) module is used to process the user's initial query into the richest, fullest query representation possible. This representation is then fed into a query converter for each search engine which, in turn, produces the richest representation usable by the selected COTS Web Search Engine(s). The search engine does its full web search and the top N-selected documents are returned and run through eQuery's full NLP document analyzer module. The full L-2-L query representation is now utilized and matched against the representation of these top-ranked documents that have been processed through the full NLP system, and a re-ranked list of documents is presented to the user or alternatively, to a selected visualization tool.
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