{"title":"Managing change in the Rufus system","authors":"P. Schwarz, Kurt A. Shoens","doi":"10.1109/ICDE.1994.283028","DOIUrl":"https://doi.org/10.1109/ICDE.1994.283028","url":null,"abstract":"Rufus is an information system that models user data with objects taken from a class system. Due to the importance of coping with changes to the schema, Rufus has adopted the conformity-based model of Melampus. This model enables Rufus to cope with schema changes more easily than traditional class- and inheritance-based data models. The paper reviews the Melampus data model and describes how it was implemented in the Rufus system. The authors show how changes to the schema can be accommodated with minimum disruption. They also review design decisions that contributed to streamlined schema evolution and compare this approach with those proposed in the literature.<<ETX>>","PeriodicalId":142465,"journal":{"name":"Proceedings of 1994 IEEE 10th International Conference on Data Engineering","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1994-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130472251","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":"Performance evaluation of grid based multi-attribute record declustering methods","authors":"Bhaskar Himatsingka, J. Srivastava","doi":"10.1109/ICDE.1994.283051","DOIUrl":"https://doi.org/10.1109/ICDE.1994.283051","url":null,"abstract":"We focus on multi-attribute declustering methods which are based on some type of grid-based partitioning of the data space. Theoretical results are derived which show that no declustering method can be strictly optimal for range queries if the number of disks is greater than 5. A detailed performance evaluation is carried out to see how various declustering schemes perform under a wide range of query and database scenarios (both relative to each other and to the optimal). Parameters that are varied include shape and size of queries, database size, number of attributes and the number of disks. The results show that information about common queries on a relation is very important and ought to be used in deciding the declustering for it, and that this is especially crucial for small queries. Also, there is no clear winner, and as such parallel database systems must support a number of declustering methods.<<ETX>>","PeriodicalId":142465,"journal":{"name":"Proceedings of 1994 IEEE 10th International Conference on Data Engineering","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1994-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127537832","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":"Fast ranking in limited space","authors":"Alistair Moffat, J. Zobel","doi":"10.1109/ICDE.1994.283064","DOIUrl":"https://doi.org/10.1109/ICDE.1994.283064","url":null,"abstract":"Ranking techniques have long been suggested as alternatives to conventional Boolean methods for searching document collections. The cost of computing a ranking is, however, greater than the cost of performing a Boolean search, in terms of both memory space and processing time. The authors consider the resources required by the cosine method of ranking, and show that, with a careful application of indexing and selection techniques, both the space and the time required by ranking can be substantially reduced. The methods described in the paper have been used to build a retrieval system with which it is possible to process ranked queries of 40 terms in about 5% of the space required by previous implementations; in as little as 25% of the time; and without measurable degradation in retrieval effectiveness.<<ETX>>","PeriodicalId":142465,"journal":{"name":"Proceedings of 1994 IEEE 10th International Conference on Data Engineering","volume":"96 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1994-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126116999","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":"Index structures for information filtering under the vector space model","authors":"T. Yan, H. Garcia-Molina","doi":"10.1109/ICDE.1994.283049","DOIUrl":"https://doi.org/10.1109/ICDE.1994.283049","url":null,"abstract":"The authors study what data structures and algorithms can be used to efficiently perform large-scale information filtering under the vector space model, a retrieval model established as being effective. They apply the idea of the standard inverted index to index user profiles. They devise an alternative to the standard inverted index, in which they, instead of indexing every term in a profile, select only the significant ones to index. They evaluate their performance and show that the indexing methods require orders of magnitude fewer I/Os to process a document than when no index is used. They also show that the proposed alternative performs better in terms of I/O and CPU processing time in many cases.<<ETX>>","PeriodicalId":142465,"journal":{"name":"Proceedings of 1994 IEEE 10th International Conference on Data Engineering","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1993-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123813274","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":"A method for transforming relational schemas into conceptual schemas","authors":"P. Johannesson, Katalin Kalman","doi":"10.1109/ICDE.1994.283030","DOIUrl":"https://doi.org/10.1109/ICDE.1994.283030","url":null,"abstract":"A major problem with currently existing database systems is that there often does not exist a conceptual understanding of the data. Such an understanding can be obtained by describing the data using a semantic data model, such as the ER model. Consequently, there is a need for methods that translate a schema in a traditional data model into a conceptual schema. We present a method for translating a schema in the relational model into a schema in a conceptual model. We also show that the schema produced has the same information capacity as the original schema. The conceptual model used is a formalization of an extended ER model, which also includes the subtype concept.<<ETX>>","PeriodicalId":142465,"journal":{"name":"Proceedings of 1994 IEEE 10th International Conference on Data Engineering","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1989-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132576852","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}