1987 IEEE Third International Conference on Data Engineering最新文献

{"title":"Automatic probabilistic knowledge acquisition from data","authors":"W. Gevarter","doi":"10.1109/ICDE.1987.7272384","DOIUrl":"https://doi.org/10.1109/ICDE.1987.7272384","url":null,"abstract":"This paper documents an outline for a computer program for extracting significant correlations of attributes from masses of data. This information can then be used to develop a knowledge base for a probabilistic “expert system.” The method determines the “best” estimate of ~oint probabilities of attributes from data put into contingency table form. A major output from the program is a general formula for calculating any probability relation associated with the data. These probability relations can be utilized to form IFTHEN rules with associated probability, needed for expert system development.","PeriodicalId":145433,"journal":{"name":"1987 IEEE Third International Conference on Data Engineering","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1987-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132339048","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Relationship between data engineering and software engineering","authors":"S. Yau","doi":"10.1109/ICDE.1987.7272359","DOIUrl":"https://doi.org/10.1109/ICDE.1987.7272359","url":null,"abstract":"Data engineering and software engineering have a very close relationship. Our ability in developing and maintaining large-scale software mainly depends on our ability to understand, analyze, use and update the enormous amount of data associated with various phases of the life cycle of the large-scale software system under consideration. Although many tools to provide useful assistance in developing and maintaining software are available, they are often not effective for large-scale software due to the complexity in dealing with the very large amount of data. One way to overcome this difficulty is to develop a knowledge-based software environment so that artificial intelligence techniques can be applied to large-scale software development and maintenance. On the other hand, the effectiveness and quality of data engineering depend upon the performance of the software engineering approaches and tools used in data engineering. In this panel session, the panelists will discuss various aspects of this subject and exchange their ideas and experiences in this area. Ample time will be available for discussion from the floor.","PeriodicalId":145433,"journal":{"name":"1987 IEEE Third International Conference on Data Engineering","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1987-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133101829","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Finer grained concurrency for the database cache","authors":"J. Moss, B. Leban, Panos K. Chrysanthis","doi":"10.1109/ICDE.1987.7272362","DOIUrl":"https://doi.org/10.1109/ICDE.1987.7272362","url":null,"abstract":"The database cache transaction recovery technique as proposed in [Elhard and Bayer 84] offers significant performance advantages for reliable database systems. However, the smallest granularity of locks it provides is the page. Here we present two schemes supporting smaller granularity. The first scheme allows maximal concurrency consistent with physical two-phase locking, with the same per-transaction I/O cost as original database cache scheme. The second scheme offers the same concurrency as the first, but features reduced I/O on commit, at the cost of some increase recovery time.","PeriodicalId":145433,"journal":{"name":"1987 IEEE Third International Conference on Data Engineering","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1987-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132467705","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Data engineering for intelligent inference","authors":"V. Lum, Sakti P. Ghosh","doi":"10.1109/ICDE.1987.7272383","DOIUrl":"https://doi.org/10.1109/ICDE.1987.7272383","url":null,"abstract":"As advanced applications become more and more demanding, the use of the data on hand becomes more and more sophisticated. In applications such as the kind in commercial banking environment, the search for data is rather simple and precise; the time constraints are not severe; statistical applications are not often used; history data is not so important; and estimates are not performed. In short, the demand to have an intelligent DB is at best minimal.","PeriodicalId":145433,"journal":{"name":"1987 IEEE Third International Conference on Data Engineering","volume":"634 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1987-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122948683","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Symbolic processing","authors":"H. Barsamian","doi":"10.1109/ICDE.1987.7272388","DOIUrl":"https://doi.org/10.1109/ICDE.1987.7272388","url":null,"abstract":"Is Symbolic processing the messenger of a new era in computing, or is it the newest hype that may eventually survive only in the encyclopedia of information processing as another passing historical reference …? Neither of these extremes however would seem to be the likely fate for symbolic processing. In reality, this technology may become the next evolutionary plateau that will open sorely missing new avenues for increasing computing efficiency, improving programming productivity and enhancing the bandwidth of man-machine interactions. As such symbolic processing presents a set of new problems, proper and timely solutions of which will determine the extent of the impact symbolic processing may eventually have on the information processing industry as a whole. One such problem seems to be the limitations of current methods for knowledge acquisitions and knowledge representation. Given the human tendency of narrowing the gap between naturally intelligent and artificially intelligent systems, the presently used tools for knowledge acquisition and representation quickly became inadequate as the knowledge domain boundaries begin to expand. Obviously, much research needs to be done in this area. Another subject of major concern is the lack of formalism and semantics of symbols for representing complex objects, concepts and relationships. Such a formalism should allow to minimize, if not eliminate ambiguities, \"shadow\" effects and contradictions in representation and interpretation, and thus contribute to the coherency of inferences when large data/knowledge bases are processed. Meanwhile full explicitness of inferencing as the ultimate goal, may always remain elusive … Design issues in the field of symbolic processing are among the most debated subjects by researchers and practitioners. Current research toward the solution of critical problems involve the whole system design space - algorithms, languages, architecture and implementation. The effective solution of these problems supported by demonstrable practical results will further enhance the commercial viability and the broad based applications of the symbolic processing technology.","PeriodicalId":145433,"journal":{"name":"1987 IEEE Third International Conference on Data Engineering","volume":"82 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1987-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124912325","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Expert system based configuration of VSAM files","authors":"K. Allgeyer, K. Kratzer","doi":"10.1109/ICDE.1987.7272368","DOIUrl":"https://doi.org/10.1109/ICDE.1987.7272368","url":null,"abstract":"The VSAM data access method supports management of sequential, relative, and index-sequential files. The latter are highly dependent on various parameters in terms of access behavior and storage overhead. Only few experts in this field are able to reasonably adjust these parameters to meet application programmers' requirements. This paper reports on the implementation of an expert system containing all relevant facts as well as heuristics for an optimal design, and providing access for application programmers via a dialog shell.","PeriodicalId":145433,"journal":{"name":"1987 IEEE Third International Conference on Data Engineering","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1986-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128923033","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The historical relational data model (HRDM) and algebra based on lifespans","authors":"J. Clifford, A. Croker","doi":"10.1109/ICDE.1987.7272420","DOIUrl":"https://doi.org/10.1109/ICDE.1987.7272420","url":null,"abstract":"Critical to the design of an historical database model is the representation of the “existence” of objects across the temporal dimension — for example, the “birth,” “death,” or “rebirth” of an individual, or the establishment or dis-establishment of a relationship. The notion of the “lifespan” of a database object is proposed as a simple framework for expressing these concepts. An object's lifespan is simply those periods of time during which the database models the properties of that object. In this paper we propose the historical relational data model (HRDM) and algebra that is based upon lifespans and that views the values of all attributes as functions from time points to simple domains. The model that we obtain is a consistent extension of the relational data model, and provides a simple mechanism for providing both time-varying data and time-varying schemes.","PeriodicalId":145433,"journal":{"name":"1987 IEEE Third International Conference on Data Engineering","volume":"67 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1986-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130601260","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}