Enhancing AIML Bots using Semantic Web Technologies
AIML [Artificial Intelligence Markup Language] is a derivative of XML [Extensible Markup Language] that enables pattern-based, stimulus-response knowledge content to be served, received and processed on the Web and offline in the manner that is presently possible with HTML [Hypertext Markup Language] and XML. AIML was designed for ease of implementation, ease of use by newcomers, and for interoperability with XML and XML derivatives such as XHTML. Software reads the AIML objects and provides application-level functionality based on their structure. The AIML interpreter is part of a larger application generically known as a bot, which carries the larger functional set of interaction based on AIML. A software module called a responder handles the human-to-bot or bot-to-bot interface work between an AIML interpreter and its object(s).
RDF [Resource Description Framework] is a language for representing information, specifically metadata, about resources in the World Wide Web. The underlying structure of any RDF expression is a collection of triples. Each triple represents a statement of a relationship between the things that it links. Each triple has three parts: a subject, an object, and a predicate (also called a property) that denotes the relationship. In many cases the triples can be used to form simple human understandable sentences.
This paper discusses a methodology and provides examples of the conversion of RDF triples to AIML topics and categories which can then be used within an AIML-based bot. The statements representing the domain knowledge can then be used in a conversation handled by the responder. The combination of these two technologies allows the knowledge represented within the RDF to be accessed interactively using natural language by a human user.
|Submitted :||6th, August 2008|