Center for Natural Language Processing

Director – Howard Turtle
Location – 335 Hinds Hall
Phone number – 315-443-4456
Emaillelmore@syr.edu

Mission

The mission of the Center for Natural Language Processing is to advance the development of human-like language understanding software capabilities for government, commercial, and consumer applications.

Objectives

  • To conduct leading-edge research and development in natural language processing and its most promising applications.
  • To secure significant government funding from those organizations that have shown vision in the field of natural language processing and have provided substantive funding to back that vision.
  • To work collaboratively with a wide range of partners to bring the center’s research into full play for a broader spectrum of users.
  • To provide meaningful research opportunities to the iSchool’s community of scholars, including faculty, graduate students, and post-doctoral researchers.

Projects

  • Understanding the Connotative Meaning of Text: Our mission is to develop and test natural language processing capabilities that can recognize, interpret, and characterize implicit levels of meaning in text without requiring human intervention, a substantial step forward in natural language understanding that would offer tremendous advantages to all its applications.
  • Improving Public Health Grey Literature Access for the Public Health Workforce: The broad, long-term objective of this project is to provide the public health workforce with improved access to high quality, highly relevant public health grey literature reports, based on the premise that such access has the potential to positively impact the quality, effectiveness, and efficiency of planning, conducting, and evaluating public health interventions.
  • DHB: Investigating the Dynamics of Free/Libre Open Source Software Development Teams: The team will be investigating the dynamics through which Free/Libre Open Source Software (FLOSS) teams develop shared mental models and the norms and rules for interaction and work processes. Three methods to investigate these processes will be integrated: natural language processing, social network analysis, and source code analysis.
  • Enhancing Access to Digital Collections using Automatic Metadata Assignment and Search Tools: The goal of the Institute of Museum and Library Services-funded MAST project is to integrate three digital library tools and services to create a new system, Metadata Assignment and Search Tool (MAST), that will enable libraries and museums to efficiently describe and disseminate their digital materials. Once integrated, these three technologies will enable collection holders – whether libraries or museums – to quickly and richly describe their digital materials to make them fully available in a digital library or searchable via web services from their own web site.
Course Schedule Black Board Apply Give About Contact