17. A method for retrieving documents related to a concept from a text corpus of stored documents comprising: for each of a set of at least four predefined semantic classes, which classes are combinable according to predefined syntactic rules in different combinations thereof to express the concept, storing a set of user-selected keywords in computer readable form on computer storage media as being associated with that class, each of at least four of the predefined semantic classes including at least five keywords, at least some of the semantic classes including keywords which are used in relevant expressions in retrieved text when the constituent notion is being conveyed and including keywords having different meanings from other keywords of the same semantic class and which are not synonymous with the other keywords of the semantic class; labeling keywords in the text corpus which belong to at least one of the predefined semantic classes; labeling pairs of labeled keywords, using a computer, which are in any one of a plurality of syntactic relationships and which meet one of the predefined syntactic rules, each of the syntactic rules identifying a pair of semantic classes comprising a respective first of the semantic classes and a respective second of the semantic classes, whereby different rules identify different pairs of semantic classes, the rule being satisfied when any first keyword from the first of the pair of semantic classes and any second keyword from the second of the pair of semantic classes are in any one of a plurality of syntactic relationships, wherein at least some of the keyword pairs are assigned a weight indicative of retrieval performance; and labeling documents in the corpus which include at least one labeled pair; and retrieving at least a portion of the documents from the corpus which include at least one labeled pair based on a ranking which takes into account the weight accorded to the keyword pairs.
19. The method of claim 17 , further comprising: using user-selected keywords to identify the text corpus within a larger text Corpus.