My research focuses on the architecture and development of speech-enabled conversational agent that relies on series of consumer-centric health ontologies and the technology that utilizes these ontologies. Human papillomavirus (HPV) vaccine, in particular, is a vaccine that inoculates individuals from certain HPV viruses responsible for adulthood cancers - cervical, head and neck cancers, etc. Where this technology could be of service is in patient-provider communication, specifically for communicating the risks and benefits of vaccines. Speech and conversational technologies are increasingly being used by consumers, with the inevitability that one day they will be integrated in health care. In this paper we describe the current version of the system, in particular discussing its portability, its reasoning capabilities, and its learning mechanism. Moreover it also includes a learning component, which ensures that the performance of the system improves over time, in response to the particular community jargon used by the end users. AquaLog combines several powerful techniques in a novel way to make sense of NL queries and to map them to semantic markup.
We say that AquaLog is portable, because the configuration time required to customize the system for a particular ontology is negligible.
AquaLog is a portable question-answering system which takes queries expressed in natural language and an ontology as input and returns answers drawn from the available semantic markup.
As semantic markup becomes ubiquitous, it will become important to be able to ask queries and obtain answers, using natural language (NL) expressions, rather than the keyword-based retrieval mechanisms used by the current search engines.
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