Intentional analysis of medical conversations for community engagement

With an explosion in proliferation of user-generated content, the productivity of search is decreasing and quality of readily available online content is deteriorating. There is an increasing need for intelligent community based systems that can understand community conversations and proactively connect users together based on community information need and interests. We describe our approach based on modeling community utterances to proactively target the community for exchange of questions and answers. We envision a system that automatically encourages user engagement and participation by prompting questions and asking to suggest answers based on user’s and community activity levels. In this paper, we analyze health forum conversations from WebMD.com and learn to classify them in different speech acts using Verbal Response Modes (VRM) theory. We describe our approach for modeling an intelligent community to engage participants based on observations from our analysis.

Short Paper: Saurav Sahay, Hua Ai and Ashwin Ram. Intentional analysis of medical conversations for community engagement. Flairs 2011, Palm Beach, Florida. www.cc.gatech.edu/faculty/ashwin/papers/er-11-01.pdf

Socio-Semantic Health Information Access

We describe Cobot, a mixed initiative socio-semantic conversational search and recommendation system for finding health information. With Cobot, users can start a real time conversation about their health concerns. Cobot then connects relevant users together in the conversation also providing contextual recommendations relevant to the conversation. Conventional search engines and content portals provide a solitary search experience inundating the health information seeker with a hoard of information often confusing and frustrating them. Cobot brings relevant healthcare information directly or through other users without any search through natural language conversation.

Read the paper: Saurav Sahay and Ashwin Ram. Socio-Semantic Health Information Access, AAAI 2011 Spring Symposium, AI and Health Communication Track.