Processing Recursion in Database Management Systems         (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 research investigates query processing and optimization            in a deductive database system.  The most important computational               challenges that arise in such a system are due to the presence of               recursively defined relations, i.e., those defined by recursive                 Horn clauses.  We will extend known algebraic models and use them               to study recursion.  We will implement several processing                       algorithms for recursion and compare their performance while                    varying the values of several important database parameters.  We                will also develop query optimization algorithms that take into                  account the important processing algorithms and, using realistic                estimates for intermediate result sizes, suggest the most                       effective access plan for the query concerned.  Our                             implementation effort will be supported by the investigation of                 several theoretical issues that arise regarding recursion in                    database systems, such as maintaining materialized relations that               are defined recursively, characterizing uniformly bounded                       recursion, and characterizing equivalence of nonlinear and linear               Horn clauses.                                                                           The importance of this research is that it leads to                     improvements in database management systems, allowing them to                   answer more complicated kinds of inquiries automatically. These                 enhanced database management systems are needed to effectively                  support new application areas, such as Computer Assisted                        Design/Manufacturing and knowledge based reasoning systems in                   artificial intelligence.
{'FirstName': 'Yannis', 'LastName': 'Ioannidis', 'PI_MID_INIT': 'E', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Yannis E Ioannidis', 'EmailAddress': 'yannis@cs.wisc.edu', 'NSF_ID': '000106346', 'StartDate': '08/15/1987', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
{'Name': 'University of Wisconsin-Madison', 'CityName': 'MADISON', 'ZipCode': '537151218', 'PhoneNumber': '6082623822', 'StreetAddress': '21 North Park Street', 'StreetAddress2': 'Suite 6301', 'CountryName': 'United States', 'StateName': 'Wisconsin', 'StateCode': 'WI', 'CONGRESSDISTRICT': '02', 'CONGRESS_DISTRICT_ORG': 'WI02', 'ORG_DUNS_NUM': '161202122', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF WISCONSIN SYSTEM', 'ORG_PRNT_DUNS_NUM': '041188822'}
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{'Code': '6856', 'Text': 'ARTIFICIAL INTELL & COGNIT SCI'}
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