Discovering Related Web Pages through Fuzzy Context Reasoning

The rapid growth of Web resources makes very difficult the task of Web search engines. Nevertheless powerful search crawlers have been developed to aid in locating unfamiliar document (by means of category, contents or subject based approaches), often queries return inconsistent results. The main lack of Web searching is in the deduction capability: nowadays Web searching put much attention in matching user's queries that are too weak to cope with the user's expressiveness. First attempts in extending searching towards deduction capability are essentially based on two-valued logic and standard probability theory. The complexity of the problem (8.4 million of Web sites), the features of the space domain (unstructured data, immature standards) demand a strong deviation from this trend. This work presents some results stemmed from a research projects where different technologies (in particular mobile agents and approximate reasoning) have been merged into an operational architecture suitable for Web searching/Web discovering. This paper discusses a different approach to Web searching where the input to the retrieval process is described through a Web page. The system reacts to this kind of query by returning a set of Web pages that reflect a similar context and deals with related arguments