Evaluation of SGML-based Information through Fuzzy Techniques

The large amount of information available and the difficulty on processing it has made knowledge management a promising area of research. Several topics are related to it, for example distributed and intelligent information retrieval, information filtering and information evaluation, which became crucial. In this paper, we focus our attention on the knowledge evaluation problem. With the aim of evaluating information coded in the standard non-proprietary format SGML (as also in XML), we propose some evaluation methods based on L-grammars which are fuzzy grammars. In particular we apply these methods to the evaluation of documents in SGML-format and to the evaluation of HTML-pages in the World Wide Web. L-grammars generate recursively enumerable L-languages, as it has been proved in Gerla ((1991), Information Sciences 53), and so they can be used to generate fuzzy languages based on extensions of the document type definitions (DTD) involved by SGML. Given a DTD, we extend its associated language by adding a judgement label. By selecting a particular label and by taking the start symbol of the grammar associated to the DTD, we can generate any DTD-compliant document with a fuzzy degree of membership derived from the judgement label. In this way we fit the computational model underlying the recursively enumerable L-languages to the process of collecting different evaluations of the same document. Finally, we outline how the generalization of these methods of evaluation can be applied in different contexts and for different roles, as for example for information filtering.