A Model of Intelligent Information Retrieval Using Fuzzy Tolerance Relations Based on Hierarchical Co-Occurrence of Words
László Tamás Kóczy, T.D. Gedeon · Studies in fuzziness and soft computing · 2000
This chapter treats a problem in connection with automatic indexing and retrieval of documents where it cannot be guaranteed that the user queries in-clude the actual words that occur in the documents that should be retrieved. Fuzzy tolerance and similarity relations will be presented and the notion of hierarchical co-occurrence is defined that allows the introduction of two or more hierarchical categories of words in the documents. If the query is based on a single keyword it is possible to extend the query to the compatibility (or equivalence) class of the queried word. So, directly matching documents can be retrieved, or a class of matching words established by some sample document collection and then docu-ments matching with words in this latter class can be retrieved. Various methods of search and retrieval will be proposed and illustrated, with the intention of real application in legal document collections. These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.