2-5 cate~ories or ooncept codes. Thus a set 0£ semantically associated natural lang~~e terms comprised 0£ synonyms, £or example, can be mapped into a single element in the index langu~e; or a single natural langu~e term which has several connotations can be identified with a set 0£ elements in~the index langu~e (homonyms mi~ht be treated in this manner). Figure 2.1 provides an illustration by means 0£ an excerpt £rom the S~ART system thesaurus. The notion 0£ a semantically based transformation on a set 0£ reco~nizable (by machine) linguistic £eatures (word or stem types, phrases, etc.) can be generalized to include a variety 0£ the 13 associations which such elements possess. The index transformation may be described in this case by considering a multi-stage mapping. The £irst step consists in mapping the document into the set 0£ basic elements which describe it, e.g. into the set 0£ word types it contains. The second step is a transformation £rom these elements into a space 0£ synonymous term groups i.e. into thesaurus categories. (The thesaurus mapping described above consists in applying these two basic transformations.) Additional transformation stages may also be de£ined. Thus generic (inclusion). relations exist among semantic elements and these may be used to de£ine a set 0£ hierarchies. A number 0£ transformation can be de£ined based on a set 0£ such relations; thus a term which includes or. which is included by a given term may be~ added to or may replace the related term in the document image. The index image 0£ a document, there£ore, can~be modified to contain terms which are generically related to those detected, but not explicitly present in the input text. Relation~s among index terms other than )