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Proceedings of the 2nd International Conference on Digital Tools & Uses Congress最新文献

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CORPUS17 CORPUS17
Simon Gabay, Alexandre Bartz, Yohann Deguin
We investigate the creation of a 17th c. French literary corpus. We present the main options regarding available standards, the training data we created and the efficiency of the models produced for OCR, spelling normalisation and lemmatisation - always with open-source solutions. We also present our encoding choices and the global logic of a corpus designed as a virtuous circle, enhancing automatically the tools that are used for its construction.
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引用次数: 1
Using quantum evolutionary based algorithm to solve materialized view selection problem 基于量子进化算法解决物化视图选择问题
Raouf Mayata, A. Boukra
A Data warehouse is a structure that stores big amount of data. This data is exploited in the best possible ways in order to improve the efficiency of decision-making. The huge volume of data makes answering queries complex and time-consuming. Therefore, materialized views are used in order to reduce the query processing time. Since materializing all views is not possible, due to space and maintenance constraints, materialized view selection became one of the crucial decisions in designing a data warehouse for optimal efficiency. In this paper, the authors propose a Quantum Evolutionary based algorithm named QEAM to solve the materialized view selection (MVS) problem with storage space constraint. The experimental results show the efficiency of the proposed algorithm compared to well-known algorithms used to solve MVS problem with storage space constraint.
数据仓库是一种存储大量数据的结构。为了提高决策效率,以最好的方式利用这些数据。庞大的数据量使得回答查询变得复杂且耗时。因此,使用物化视图是为了减少查询处理时间。由于空间和维护方面的限制,不可能实现所有视图的物化,因此物化视图选择成为设计数据仓库以获得最佳效率的关键决策之一。针对存储空间受限的物化视图选择问题,提出了一种基于量子进化的QEAM算法。实验结果表明,该算法与常用的具有存储空间约束的MVS算法相比,具有较高的效率。
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引用次数: 0
Proceedings of the 2nd International Conference on Digital Tools & Uses Congress 第二届国际数字工具与应用会议论文集
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引用次数: 0
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Proceedings of the 2nd International Conference on Digital Tools & Uses Congress
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