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Titlebook: Beyond Databases, Architectures, and Structures; 10th International C Stanislaw Kozielski,Dariusz Mrozek,Daniel Kostrzew Conference proceed

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發(fā)表于 2025-3-21 16:12:04 | 只看該作者 |倒序瀏覽 |閱讀模式
期刊全稱Beyond Databases, Architectures, and Structures
期刊簡稱10th International C
影響因子2023Stanislaw Kozielski,Dariusz Mrozek,Daniel Kostrzew
視頻videohttp://file.papertrans.cn/186/185163/185163.mp4
學(xué)科分類Communications in Computer and Information Science
圖書封面Titlebook: Beyond Databases, Architectures, and Structures; 10th International C Stanislaw Kozielski,Dariusz Mrozek,Daniel Kostrzew Conference proceed
影響因子This book constitutes the refereed proceedings of the 10th IEEE International Conference Beyond Databases, Architectures, and Structures, BDAS 2014, held in Ustron, Poland, in May 2014. This book consists of 56 carefully revised selected papers that are assigned to 11 thematic groups: query languages, transactions and query optimization; data warehousing and big data; ontologies and semantic web;computational intelligence and data mining; collective intelligence, scheduling, and parallel processing; bioinformatics and biological data analysis; image analysis and multimedia mining; security of database systems; spatial data analysis; applications of database systems; Web and XML in database systems.
Pindex Conference proceedings 2014
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,The exIWO Metaheuristic – A Recapitulation of the Research on the Join Ordering Problem,zed by both the hybrid strategy of the search space exploration and three variants of selection of individuals as candidates for next population. The nub of the problem was recalled along with details of adaptation of the exIWO including representation of a single solution and transformation of an i
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Granular Indices for HQL Analytic Queries,of records. The usual technique to reduce their run-time is the materialization of partial aggregates of base data. In previous papers we have proposed the concept of metagranules, i.e. partially ordered aggregations of the fact table. When a query is posed, the actual aggregation level will be dete
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Data Quality Issues Concerning Statistical Data Gathering Supported by Big Data Technology,cal data gathering on job offers was used. This example allowed comparing data quality issues in two different methods of data gathering: traditional statistical surveys vs. Big Data technology. The case study shows that there are lots of barriers related to data quality when using Big Data technolo
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