1. An information mining method, comprising: receiving product-related queries, and respective product-related information from various unstructured text sources; extracting multiple key-phrases from the received product information and queries; transforming each of the extracted key-phrases into a unique numerical representation; generating two or more layers of contextual relation maps by mapping the transformed product information and query key phrases, respectively, to two-dimensional maps using a self-organizing map and a function approximation neighborhood technique; forming phrase clusters for each of the generated contextual relation maps; constructing key phrase frequency histograms consisting of the frequency of occurrences of product related key phrases and query-related key-phrases, respectively, from each of the generated contextual relation maps; generating two or more two-dimensional structured document maps of the product and queries from each of the corresponding constructed key phrase frequency histograms and the generated contextual relation maps using function approximation neighborhood technique in the self organizing map; and selecting answers to the received queries based on masking the generated product and query two-dimensional structured maps, respectively.