This paper addresses the issue of locating relevant information in a network of heterogeneous, unfederated information bases of various types, including structured databases, text, audio, picture and video files. The problem is to determine where the required information resides in a network, in locations unknown to the user. The objective is to construct a user-friendly, intelligent, search and routing mechanism in order to find the most relevant information bases in the network. We introduce a mechanism for presenting queries, routing queries, updating knowledge, and learning in a metaknowledge base (MKB). This has been named the metaknowledge-based intelligent routing system (MIRS). MIRS finds the location of the desired information by its ability to `understand' the user's query and to access information by content, rather than by address. MIRS behaves like a distributed search engine, working with a distributed metaknowledge index-file. There is no need for periodic web-crawling, web-robots, or agents of any sort. The network itself encapsulates the knowledge and routing algorithms that provide the user access-by-content to the relevant information. Contrary to web servers, the specific MIRS servers are not linked by hypertext links, but rather by knowledge links, randomly acquired or expertly built. The system also differs from the usual search engines in that it is capable of handling different types of media (e.g., text, database, multimedia) and applies natural language parsing techniques to understand the intention of the user, as well as potentially use a user-profile to enhance the original query before distributing it over the network, The `metadata' describing the information bases are spread across a network of routing and information servers and are modified as a result of search operations and introduction of new information bases into the system.
ASJC Scopus subject areas
- Information Systems and Management