Chinatsu Aone

TL;DR: Improvements to the infrastructure, both in system architecture and the supporting set of tools, and the introduction of trainable learningbased modules are made for MUC-7.

TL;DR: A scalable summarization system which takes advantage of robust NLP technology such as corpus-based statlshcal NLP techmques, information extractmn and readily available on-hne resources is described.

TL;DR: A trainable and scalable summarization system which utilizes features derived from information retrieval, information extraction, and NLP techniques and on-line resources and is demonstrated system scalability by reporting results on the best combination of summarization features for different document sources.

TL;DR: This paper describes RoboTag, an advanced prototype for a machine learningbased multilingual information extraction system, and describes a general client/server architecture used in learning from observation and presents experimental results which compare RoboTag to both human-tagged keys and to the best hand-coded rule systems.

TL;DR: This work performs an experimental evaluation of the methods for name transliteration from three languages into English, and compares the methods experimentally to a state-of-the-art joint probabilistic modeling approach.