Semantics and quantification in natural language question answering
Readings in natural language processing
Instance-Based Learning Algorithms
Machine Learning
WebMate: a personal agent for browsing and searching
AGENTS '98 Proceedings of the second international conference on Autonomous agents
Transition network grammars for natural language analysis
Communications of the ACM
Discovering semantic biomedical relations utilizing the Web
ACM Transactions on Knowledge Discovery from Data (TKDD)
Implicit affinity networks and social capital
Information Technology and Management
PLOW: a collaborative task learning agent
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 2
Social network activity and social well-being
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
The anatomy of a large-scale social search engine
Proceedings of the 19th international conference on World wide web
Supporting synchronous social q&a throughout the question lifecycle
Proceedings of the 20th international conference on World wide web
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We develop an innovative approach to delivering relevant information using a combination of socio-semantic search and filtering approaches. The goal is to facilitate timely and relevant information access through the medium of conversations by mixing past community specific conversational knowledge and web information access to recommend and connect users and information together. Conversational Information Access is a socio-semantic search and recommendation activity with the goal to interactively engage people in conversations by receiving agent supported recommendations. It is useful because people engage in online social discussions unlike solitary search; the agent brings in relevant information as well as identifies relevant users; participants provide feedback during the conversation that the agent uses to improve its recommendations.