Signature File Methods for Text Data Bases (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': 'Maria Zemankova', 'PO_EMAI': None, 'PO_PHON': None}
This research develops the design and analysis of efficient                 searching  methods for text data bases.  It utilizes a new                      method,  called signature files, which works well for archival                  applications with very active updating. The method is especially                suitable for optical disks. Specifically, signature files are                   compared with other indexing methods analytically and through                   simulation. Several alternative signature extraction methods are                implemented and evaluated to verify analytical results, and                     integrated signature methods, which cover both the text itself                  and "keyword" attributes, are developed. To perform realistic                   experiments, a prototype retrieval system is used, which stores                 and retrieves abstracts of technical articles.  This prototype is               available to researchers at the University of Maryland, to assist               them with literature searching and to give feedback to the system               designers about what capabilities are needed and how the system                 is used.                                                                                There is an enormous and increasing amount of scientific                knowledge captured in the form of published articles and reports.               This "text database" is far too large to be effectively used                    without computer assistance.  Consequently, research on automatic               retrieval methods, which allow effective and extensive searching                to be done with computer systems, is of paramount scientific and                practical importance.
{'FirstName': 'Christos', 'LastName': 'Faloutsos', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Christos Faloutsos', 'EmailAddress': 'christos@cs.cmu.edu', 'NSF_ID': '000236167', 'StartDate': '07/01/1987', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
{'Name': 'University of Maryland, College Park', 'CityName': 'COLLEGE PARK', 'ZipCode': '207425100', 'PhoneNumber': '3014056269', 'StreetAddress': '3112 LEE BUILDING', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Maryland', 'StateCode': 'MD', 'CONGRESSDISTRICT': '04', 'CONGRESS_DISTRICT_ORG': 'MD04', 'ORG_UEI_NUM': 'NPU8ULVAAS23', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF MARYLAND, COLLEGE PARK', 'ORG_PRNT_UEI_NUM': 'NPU8ULVAAS23'}
{'Name': None, 'CityName': None, 'StateCode': None, 'ZipCode': None, 'StreetAddress': None, 'CountryCode': None, 'CountryName': None, 'StateName': None, 'CountryFlag': None, 'CONGRESSDISTRICT': None, 'CONGRESS_DISTRICT_PERF': '""'}
[{'Code': '6855', 'Text': 'INFORMATION & KNOWLEDGE MANAGE'}, {'Code': '6856', 'Text': 'ARTIFICIAL INTELL & COGNIT SCI'}, {'Code': '9120', 'Text': 'CROSS-DIRECTORATE PROGRAMS'}, {'Code': '9145', 'Text': 'SPECIAL PROGRAMS-RESERVE'}]
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=1986&All=true', 'xml': '8616833.xml'}