23. A search engine stored on a computer readable storage medium, having stored thereon instructions for extracting terms from a query, comprising machine executable code which when executed by at least one machine, causes the machine to: generate a query analyser for processing a query to assign respective weights to terms of said query based on the grammatical structure of the query and the meaning of the terms of the query and to generate a query vector including said weights; generate an index network responsive to said query vector to output indices to data in response to said query, said index network being a self generating neural network having nodes of weight vectors representing categories and terms of said data, said nodes further including pointers to other nodes, and leaf nodes of said network each including an index to said data; and generate a feature extractor for extracting said indices and respective terms of said data as term weight pairs, the weights of the pairs being based on the importance and uniqueness of component ngrams of the terms of an indexed document and the terms being extracted on the basis of the distribution of ngrams in a document space of index documents of said data; and wherein said neural network is generated on the basis of training examples including said term weight pairs, and the format of said query vectors and weights vectors of said network is generated on the basis of said training examples.
23. A search engine stored on a computer readable storage medium, having stored thereon instructions for extracting terms from a query, comprising machine executable code which when executed by at least one machine, causes the machine to: generate a query analyser for processing a query to assign respective weights to terms of said query based on the grammatical structure of the query and the meaning of the terms of the query and to generate a query vector including said weights; generate an index network responsive to said query vector to output indices to data in response to said query, said index network being a self generating neural network having nodes of weight vectors representing categories and terms of said data, said nodes further including pointers to other nodes, and leaf nodes of said network each including an index to said data; and generate a feature extractor for extracting said indices and respective terms of said data as term weight pairs, the weights of the pairs being based on the importance and uniqueness of component ngrams of the terms of an indexed document and the terms being extracted on the basis of the distribution of ngrams in a document space of index documents of said data; and wherein said neural network is generated on the basis of training examples including said term weight pairs, and the format of said query vectors and weights vectors of said network is generated on the basis of said training examples. 44. A search engine as claimed in claim 23 , wherein said neural network is a self generating neural network and the format of said query vectors and vectors of nodes of said network is generated on the basis of said training examples.