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作者: informed    時間: 2025-3-21 18:01
書目名稱Granular-Relational Data Mining影響因子(影響力)




書目名稱Granular-Relational Data Mining影響因子(影響力)學(xué)科排名




書目名稱Granular-Relational Data Mining網(wǎng)絡(luò)公開度




書目名稱Granular-Relational Data Mining網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Granular-Relational Data Mining被引頻次




書目名稱Granular-Relational Data Mining被引頻次學(xué)科排名




書目名稱Granular-Relational Data Mining年度引用




書目名稱Granular-Relational Data Mining年度引用學(xué)科排名




書目名稱Granular-Relational Data Mining讀者反饋




書目名稱Granular-Relational Data Mining讀者反饋學(xué)科排名





作者: 積極詞匯    時間: 2025-3-21 20:25

作者: connoisseur    時間: 2025-3-22 00:48

作者: formula    時間: 2025-3-22 07:03
Rough-Granular Computingat is adapted to data stored in a relational databases. The chapter also defines a range of similarity measures for relational data. They are used in the construction of one of the tolerance rough set model components, i.e. the uncertainty function.
作者: ALT    時間: 2025-3-22 10:52
Relation-Based Granulesress richer knowledge about relational data. The chapter also shows that the generation of patterns can be accelerated thanks to using an alternative representation of relational data constructed on the basis of relation-based granules.
作者: 符合規(guī)定    時間: 2025-3-22 15:18
Compound Approximation Spacesinformation systems and the tolerance rough set model extended to a relational case. The chapter also shows that in constrained compound approximations spaces it is possible to approximate not only a combination of concepts, each of which is defined in one database table, but also the relationships
作者: 符合規(guī)定    時間: 2025-3-22 18:21
Conclusions of one of the frameworks depending on factors such as data structure and pattern representation. It also shows the contribution of settlement of relational data mining in the paradigm of granular computing.
作者: 變色龍    時間: 2025-3-22 21:12

作者: 火光在搖曳    時間: 2025-3-23 04:50

作者: COWER    時間: 2025-3-23 08:25

作者: 易改變    時間: 2025-3-23 11:55

作者: badinage    時間: 2025-3-23 17:43

作者: Esalate    時間: 2025-3-23 21:06
https://doi.org/10.1007/978-94-011-1494-3information systems and the tolerance rough set model extended to a relational case. The chapter also shows that in constrained compound approximations spaces it is possible to approximate not only a combination of concepts, each of which is defined in one database table, but also the relationships
作者: 小口啜飲    時間: 2025-3-24 00:47
G. M. Klump,R. J. Dooling,W. C. Stebbins of one of the frameworks depending on factors such as data structure and pattern representation. It also shows the contribution of settlement of relational data mining in the paradigm of granular computing.
作者: 設(shè)施    時間: 2025-3-24 02:57

作者: 客觀    時間: 2025-3-24 06:45

作者: Binge-Drinking    時間: 2025-3-24 11:19

作者: 交響樂    時間: 2025-3-24 17:38

作者: 威脅你    時間: 2025-3-24 20:16

作者: 音樂學(xué)者    時間: 2025-3-25 01:14

作者: 陰謀    時間: 2025-3-25 03:49
G. M. Klump,R. J. Dooling,W. C. Stebbins of one of the frameworks depending on factors such as data structure and pattern representation. It also shows the contribution of settlement of relational data mining in the paradigm of granular computing.
作者: enmesh    時間: 2025-3-25 08:08

作者: 打包    時間: 2025-3-25 12:49

作者: 驕傲    時間: 2025-3-25 16:50
Association Discovery and Classification Rule Mininghe general granular computing framework for mining relational data. The chapter also shows that the time complexity of generating rules from a granular representation of relational data can be decreased.
作者: 滋養(yǎng)    時間: 2025-3-25 22:14
Rough-Granular Computingat is adapted to data stored in a relational databases. The chapter also defines a range of similarity measures for relational data. They are used in the construction of one of the tolerance rough set model components, i.e. the uncertainty function.
作者: contrast-medium    時間: 2025-3-26 03:13
Relation-Based Granulesress richer knowledge about relational data. The chapter also shows that the generation of patterns can be accelerated thanks to using an alternative representation of relational data constructed on the basis of relation-based granules.
作者: Distribution    時間: 2025-3-26 06:02
Compound Approximation Spacesinformation systems and the tolerance rough set model extended to a relational case. The chapter also shows that in constrained compound approximations spaces it is possible to approximate not only a combination of concepts, each of which is defined in one database table, but also the relationships that occur among the concepts.
作者: 充足    時間: 2025-3-26 11:20

作者: Geyser    時間: 2025-3-26 16:20
Quantification of Behavioural Processes,This chapter provides an introduction to the fields of relational data mining and granular computing. It also reviews research at the intersection of both fields. Besides, a brief analysis of the problem of constructing a granular computing framework for mining relational data is given.
作者: 尊敬    時間: 2025-3-26 18:54
Neuroendocrine Markers of CNS Drug Effects,This chapter provides a general framework for analyzing and processing relational data in a granular computing environment. It introduces compound information systems for relational data. It also extends an attribute-value language for defining relational patterns.
作者: CAMEO    時間: 2025-3-26 21:25
A. E. Tattersfield,J. B. L. HowellThis chapter provides a methodology for upgrading a granular data mining framework to a relational case. The framework enables to discover knowledge from relational data that is expressed by extended attribute-value patterns. A procedure for translating such patterns into a relational language is also given.
作者: 完成才能戰(zhàn)勝    時間: 2025-3-27 04:01

作者: 惡臭    時間: 2025-3-27 05:48
Compound Information SystemsThis chapter provides a general framework for analyzing and processing relational data in a granular computing environment. It introduces compound information systems for relational data. It also extends an attribute-value language for defining relational patterns.
作者: 是剝皮    時間: 2025-3-27 12:24
From Granular-Data Mining Framework to Its Relational VersionThis chapter provides a methodology for upgrading a granular data mining framework to a relational case. The framework enables to discover knowledge from relational data that is expressed by extended attribute-value patterns. A procedure for translating such patterns into a relational language is also given.
作者: Gobble    時間: 2025-3-27 14:03

作者: 激怒    時間: 2025-3-27 19:43

作者: 感染    時間: 2025-3-28 01:56
Peter Dehnbostel,Hans-Jürgen Lindemann tool, HyTech. HyTech is a symbolic model checker for liner hybrid automata, and we transformed an atomic DEV&DESS model into linear hybrid automata. We are now developing translation rules from DEV&DESS models, including a coupled DEV&DESS, into linear hybrid automata, through various case studies.
作者: 摘要記錄    時間: 2025-3-28 04:32
Aromatic Hydrocarbon Degradation: A Molecular Approach,is not surprising then that due to the ubiquitous nature and increasing concentrations of aromatic hydrocarbons microorganisms can be found that have the ability to degrade these compounds. The varied mechanisms by which microorganisms utilize aromatic hydrocarbons as carbon and energy sources have been the focus of several reviews (4–10).
作者: 指數(shù)    時間: 2025-3-28 07:12

作者: UTTER    時間: 2025-3-28 13:31
Robert D. Richtmyerre for autonomy on the part of subnational political communities. As a result of decentralization reforms, the evolution of EU policies and, more generally, the increasing globalization of the overall economic context, the central administrative organs of Western states have lost their monopoly on p
作者: LATER    時間: 2025-3-28 18:28

作者: AVOW    時間: 2025-3-28 22:46

作者: 吞沒    時間: 2025-3-29 00:38

作者: 分離    時間: 2025-3-29 06:02

作者: Minikin    時間: 2025-3-29 07:39
Derrida and the (IM)Possibilities of JusticeNach S. 109, Gleichung (5) ist für ideale Gase ..




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