Natural Language Processing

Core Research Area in Natural Language Processing & Information Retrieval

Natural language processing and information retrieval constitute a major area of research and graduate study in the Department of Computer and Information Sciences at the University of Delaware. Current research interests center on strategies for understanding and the generation of descriptions of multimodal documents (i.e., documents containing information graphics), anaphora understanding and generation, , the development of robust dialogue systems, retrieval of novel and diverse URLs in web search, search over sessions of user interactions, electronic health record retrieval and analysis, statistical and corpus-based approaches to natural language processing, experimental design and statistical analysis for NLP and IR, text mining of life sciences documents, text summarization, and applying natural language processing techniques to assistive technologies for people with disabilities (particularly those with severe speech or sight impairments).

Members of our NLP group have served on or currently serve on the editorial boards of ACM Transactions on Information Systems, ACM Transactions on Accessible Computing, Computational Linguistics Journal, Information Retrieval, International Journal of Human-Computer Studies, ISRN Artificial Intelligence, Journal of Dialog Systems, Grammars and User Modeling and User-Adapted Interaction. They have served for many years as officers of the Association for Computational Linguistics, have served as general and program chair for several major conferences, and extensively serve on program committees and as workshop organizers. Research projects have been supported by grants from the National Science Foundation, the National Institutes of Health, the National Institute for Disability Research and Rehabilitation, National Institute of Food and Agriculture (USDA), and the US Army Research Lab.

Current Faculty

  • Timothy Bunnell, Research Associate Professor (joint appointment with Linguistics & Cognitive Science): Speech synthesis; Speech processing; Biological signal interfaces; Neural networks.
  • Sandra Carberry, Professor: Intelligent interfaces; Information retrieval; Natural language understanding; Response generation; Dialogue systems; User modeling; Augmentative communication systems.
  • Ben Carterette, Assistant Professor: Information retrieval; Experimental design; Statistical methods; Scientific methodology.
  • Daniel Chester, Associate Professor (joint appointment with Linguistics & Cognitive Science): Parsing.
  • Kathleen McCoy, Professor (joint appointment with Linguistics & Cognitive Science): Natural language processing; Text generation; Discourse phenomena; Sentence generation; Assistive technologies; Augmentative and alternative communication; Computer-aided language learning.
  • Vijay Shanker, Professor: Natural language processing; Parsing; Biomedical literature mining; Information extraction; Machine learning.
  • Hagit Shatkay, Associate Professor (joint appointment with Center for Bioinformatics and Computational Biology, and with Biomedical Engineering): Biomedical Text Mining, Information Retrieval, Machine Learning.

Courses

  • CISC 681 Introduction to Artificial Intelligence
  • CISC 683 Introduction to Data Mining
  • CISC 689 Introduction to Information Retrieval
  • CISC 689 Machine Learning
  • CISC 882 Natural Language Processing
  • CISC 883 Natural Language Generation
  • CISC 885 Discourse and Dialogue
  • CISC 889 Advanced Topics: Applications of Natural Language Processing
  • CISC 889 Advanced Topics: Empirical Methods in Discourse
  • CISC 889 Advanced Topics: Information Retrieval
  • CISC 889 Advanced Topics: Empirical Methods for CS
  • CISC 889 Advanced Topics: Spoken Language Processing
  • CISC 889 Advanced Topics: Statistical Approaches to NLP
  • CISC 889 Advanced Topics: Information Retrieval
  • LING 609 Syntax I
  • LING 610 Syntax II
  • LING 691 Semantics
  • LING 696 Psycholinguistics
Laboratories - Natural Language Processing

Human Language Technologies Laboratory

100 Elkton Road, Professors Sandra Carberry and Kathy McCoy.

The Human Language Technology Laboratory is an umbrella for two language-related laboratories: disabilities technology and discourse. The laboratory closely collaborates with the Statistical Information Retrieval Laboratory and the Text Mining Laboratory.

The Disabilities Technology Laboratory, directed by Kathy McCoy, develops intelligent interfaces for people with disabilities that affect their ability to communicate. The ICICLE System is an intelligent English grammar checker and tutor for people who are deaf. Other projects assist people who have special communication needs. We make “talking with” a computer faster and more natural. Another project is to help a person who has visual impairments “scan” a text to find the area relevant to answering a question.

The Discourse Laboratory, under the direction of Sandra Carberry, addresses problems related to discourse and dialogue. The Graphs project treats information graphics (bar charts, line graphs, etc.) as a form of discourse with a communicative goal. We are applying language understanding and generation techniques to index, store, and retrieve graphics from a digital library, to develop an interactive dialogue system that conveys the content of graphics via speech to individuals with sight impairments, and to develop an interactive graph design assistant that will critique graphs with the objective of improving them so that they achieve their communicative goal. Current collaborators include Dr. Stephanie Elzer (Millersville University), Dr. Dan Chester, and graduate students.

Statistical Information Retrieval Laboratory

77/79 East Delaware Ave, Professor Ben Carterette.

The Statistical Information Retrieval Laboratory pursues novel models of information organization, storage, access, retrieval, and integration using statistical and information-theoretic approaches. One of the key problems in developing such models is that optimizing and evaluating their utility requires human input. We aim to minimize the human cost, or to accomplish much more with an allotted cost, thereby allowing research and development to proceed much faster.

Text Mining Laboratory

102 Smith Hall, Professor Vijay Shanker.

The Text Mining Laboratory, directed by Vijay Shanker, is concerned with the development of language technology algorithms to assist scientists to rapidly access relevant information from research literature. Projects include the extraction of targeted information, retrieval of relevant textual passages, and assistance in the knowledge discovery process. A related project involves rapid adaptation of language processing tools that were developed for a general domain to be used in a specific domain. A third project involves multi-disciplinary effort that integrates natural language cues found in large software programs and program analysis for multiple software development and maintenance tasks.

Research Natural Language Processing