In a full-text natural-language retrieval system, frequent need for automatic hngulst~c analysis arises, e.g for keyword expansion in a search process, content analysis, or automatic construction of concordances The avadablhty of sophisticated hngulstic tools, which is highly desirable for languages such as Enghsh, is quite imperative for, say, Semmc languages, whose complex morphological structure renders simple-minded and approximate soluuons such as suffix stripping totally useless.Sophisticated tools were designed and constructed via the fusion of grammatical analysis and grammatical synthesis, resulting in a set of global files which provide in some sense a complete grammatical and lexlcal description of the language These files induce a set of local files which adapt to the database at hand and permit flexible on-hne morphological analysis.

AaSTRACT.In a full-text natural-language retrieval system, local feedbacl~ is the process of formulating a new ~mproved search based on clustering terms from the documents returned m a previous search of any given query Experiments were run on a database of US patents It ~s concluded that m contrast toglobalclustermg, where the size of matrices hmmts apphcatmns to small databases and improvements are doubtful, local clustering is practical also for large databases and appears to improve overall performance, especially tf metrical constraints and weighting by proximity are embedded m the local feedback The local methods adapt themselves to each mdwtdual search and produce useful searchonymsterms which are "synonymous" m the context of one query Searchonyms lead to new ~mproved search formulahons both via manual and vm automahc feedback