The construction of fuzzy relational maps in information retrieval

One of the major problems in automatic indexing and retrieval of documents is that usually user queries will not include all the relevant words that occur in the documents which should be retrieved. Also it often happens that the same query word with different meanings occurs in different contexts from that expected by the querying person. In order to achieve better recall and higher precision, fuzzy tolerance and similarity relations were introduced based on the counted or estimated values of (hierarchical) co-occurrence frequencies. This study addresses the problem of how these relations can be generated from the values of occurrence frequencies, especially as these are based on possibilistic rather than probabilistic measures, and also how the relations can be implemented by fuzzy relevance matrices.