Organizing Lexical Knowledge for Natural Language           Information Retrieval (Computer and Information Science)
{'Code': '05020000', 'Directorate': {'Abbreviation': 'CSE', 'LongName': 'Direct For Computer & Info Scie & Enginr'}, 'Division': {'Abbreviation': 'IIS', 'LongName': 'Div Of Information & Intelligent Systems'}}
{'SignBlockName': 'MICHELE R. JOHNSON', 'PO_EMAI': None, 'PO_PHON': None}
This project represents an integrated effort by researchers             working in the areas of information storage and retrieval,                      computational linguistics, and artificial intelligence (E.A. Fox and            J.T. Nutter at Virginia Tech, and N.M. Evans at IIT) to organize                lexical knowledge so that more effective interactive information                retrieval will be possible.  A large English lexicon (i.e., a                   knowledge base integrating various kinds of information about words,            their usage and meaning) will be created, and methods will be                   developed to use that lexicon to improve the effectiveness of online            information retrieval systems.  This lexicon will be used as an                 essential part of experimental tests of two knowledge based                     information retrieval systems, enabling empirical evaluation of the             effectiveness of various approaches to interactively using an                   English lexicon to support information retrieval.                                       The importance of this research is that the amount of                   information available today in the form of documents has grown far              beyond the ability of any individual person to manage without                   computer assistance. This work, bringing together strategies from               artificial intelligence, natural language processing, and                       information retrieval, will result in far more powerful,                        knowledge-based computer systems able to act as intelligent                     "assistants" to help people effectively access the information                  available to them in documents.
{'FirstName': 'Martha', 'LastName': 'Evens', 'PI_MID_INIT': 'W', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Martha W Evens', 'EmailAddress': 'evens@iit.edu', 'NSF_ID': '000100388', 'StartDate': '09/01/1987', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
{'Name': 'Illinois Institute of Technology', 'CityName': 'Chicago', 'ZipCode': '606163717', 'PhoneNumber': '3125673035', 'StreetAddress': '10 West 35th Street', 'StreetAddress2': 'Suite 7D71', 'CountryName': 'United States', 'StateName': 'Illinois', 'StateCode': 'IL', 'CONGRESSDISTRICT': '01', 'CONGRESS_DISTRICT_ORG': 'IL01', 'ORG_DUNS_NUM': '042084434', 'ORG_LGL_BUS_NAME': 'ILLINOIS INSTITUTE OF TECHNOLOGY', 'ORG_PRNT_DUNS_NUM': '042084434'}
{'Name': None, 'CityName': None, 'StateCode': None, 'ZipCode': None, 'StreetAddress': None, 'CountryCode': None, 'CountryName': None, 'StateName': None, 'CountryFlag': None, 'CONGRESSDISTRICT': None, 'CONGRESS_DISTRICT_PERF': '""'}
{'Code': '6856', 'Text': 'ARTIFICIAL INTELL & COGNIT SCI'}
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=1987&All=true', 'xml': '8704619.xml'}