A Persistent Feature-Object Database for Intelligent Text Archive Systems

This paper describes an intelligent text archive system in which typed feature structures are embedded. The aim of the system is to associate feature structures with regions in text, to make indexes for efficient retrieval, to allow users to specify both structure and proximity, and to enable inference on typed feature structures embedded in text. We propose a persistent mechanism for storing typed feature structures and the architecture of the text archive system.

• Type: Conference
• Year: 2004
• Where: IJCNLP
• Authors: Takashi Ninomiya, Jun-ichi Tsujii, Yusuke Miyao
• Keywords: IJCNLP 2004, Intelligent Text Archive, Text Archive, Typed Feature Structures