Cross-document summarization by concept classification
SIGIR '02 Proceedings of the 25th annual international ACM SIGIR conference on Research and development in information retrieval
A self-learning universal concept spotter
COLING '96 Proceedings of the 16th conference on Computational linguistics - Volume 2
In question answering, two heads are better than one
NAACL '03 Proceedings of the 2003 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology - Volume 1
Automated judgment of document qualities: Research Articles
Journal of the American Society for Information Science and Technology
HITIQA: towards analytical question answering
COLING '04 Proceedings of the 20th international conference on Computational Linguistics
Automatic generation of information-seeking questions using concept clusters
ACLShort '09 Proceedings of the ACL-IJCNLP 2009 Conference Short Papers
Hi-index | 0.00 |
In this paper we describe the analytic question answering system HITIQA (High-Quality Interactive Question Answering) which has been developed over the last 2 years as an advanced research tool for information analysts. HITIQA is an interactive open-domain question answering technology designed to allow analysts to pose complex exploratory questions in natural language and obtain relevant information units to prepare their briefing reports. The system uses novel data-driven semantics to conduct a clarification dialogue with the user that explores the scope and the context of the desired answer space. The system has undergone extensive hands-on evaluations by a group of intelligence analysts representing various foreign intelligence services. This evaluation validated the overall approach in HITIQA but also exposed limitations of the current prototype.