標(biāo)題: Titlebook: Big Data Analytics and Knowledge Discovery; 19th International C Ladjel Bellatreche,Sharma Chakravarthy Conference proceedings 2017 Springe [打印本頁] 作者: EVOKE 時間: 2025-3-21 18:25
書目名稱Big Data Analytics and Knowledge Discovery影響因子(影響力)
書目名稱Big Data Analytics and Knowledge Discovery影響因子(影響力)學(xué)科排名
書目名稱Big Data Analytics and Knowledge Discovery網(wǎng)絡(luò)公開度
書目名稱Big Data Analytics and Knowledge Discovery網(wǎng)絡(luò)公開度學(xué)科排名
書目名稱Big Data Analytics and Knowledge Discovery被引頻次
書目名稱Big Data Analytics and Knowledge Discovery被引頻次學(xué)科排名
書目名稱Big Data Analytics and Knowledge Discovery年度引用
書目名稱Big Data Analytics and Knowledge Discovery年度引用學(xué)科排名
書目名稱Big Data Analytics and Knowledge Discovery讀者反饋
書目名稱Big Data Analytics and Knowledge Discovery讀者反饋學(xué)科排名
作者: septicemia 時間: 2025-3-21 21:15 作者: 引水渠 時間: 2025-3-22 02:57 作者: 使成核 時間: 2025-3-22 04:39 作者: 折磨 時間: 2025-3-22 10:15 作者: ARIA 時間: 2025-3-22 15:55
https://doi.org/10.1007/978-1-4842-2382-6the issues related to the 5 Vs (Volume, Velocity, Variety, Veracity, and Value). So it is mandatory to support the designer through automatic techniques able to quickly produce a multidimensional schema using and integrating several data sources, which can be also unstructured and, therefore, need a作者: FRET 時間: 2025-3-22 17:27
https://doi.org/10.1007/978-1-4842-2382-6tics. The more complex they become, the more pressing the need for automated optimization solutions. Optimizing data flows comes in several forms, among which, optimal task ordering is one of the most challenging ones. We take a practical approach; motivated by real-world examples, such as those cap作者: 向外 時間: 2025-3-23 00:05
https://doi.org/10.1007/978-1-4842-6203-0 as open and machine-readable Linked Data. Although this approach allows easier data access and consumption, appropriate mechanisms are still needed to perform proper comparisons of statistical data. Indeed, the lack of an explicit representation of how statistical measures are calculated still hind作者: Coordinate 時間: 2025-3-23 04:44
https://doi.org/10.1007/978-1-4842-6203-0concurrent data access. The large number of users pose multiple query optimization problems. In a distributed data warehousing system such as Hadoop/Hive, queries are evaluated one at a time and processed with the MapReduce paradigm. The massive query execution usually overloads and slows down the e作者: 不利 時間: 2025-3-23 08:35
Further Case Studies on the People Theme and pay-as-you-go features of cloud computing. However, most data are sensitive to some extent, and data privacy remains one of the top concerns to DBaaS users, for obvious legal and competitive reasons. In this paper, we survey the mechanisms that aim at making databases secure in a cloud environm作者: CYT 時間: 2025-3-23 13:44 作者: syring 時間: 2025-3-23 16:46
A Specimen Case Study for Analysis as NoSQL databases that were created in response to the needs for better scalability, higher flexibility and faster data access. These systems have proven their efficiency to store and query Big Data. Unfortunately, only few works have presented approaches to implement conceptual models describing 作者: 徹底明白 時間: 2025-3-23 21:59 作者: 輕而薄 時間: 2025-3-24 02:06 作者: cogent 時間: 2025-3-24 04:41
Principles of structured learning,f big data. A prime source of these complex big data is the social network, in which users are often linked by some interdependencies such as friendships and follower-followee relationships. These interdependencies can be uncertain and imprecise. Moreover, as the social network keeps growing, there 作者: forbid 時間: 2025-3-24 06:50 作者: 蒼白 時間: 2025-3-24 11:06
https://doi.org/10.1007/978-1-4842-8076-8 transportation. A particular interesting geometric pattern is exhibited by the Einstein cross, which is an astronomical phenomenon in which a single quasar is observed as four distinct sky objects when captured by earth telescopes. Finding such crosses, as well as other geometric patterns, collecti作者: placebo-effect 時間: 2025-3-24 17:04 作者: 躺下殘殺 時間: 2025-3-24 19:42
Introducing Cisco Unified Computing Systems, e.g., those considered by state-of-the-art data flow optimization techniques, do not accurately reflect the . of real data flow execution in these execution environments. This is mainly due to the fact that the impact of parallelism, and more specifically, the impact of concurrent task execution 作者: enfeeble 時間: 2025-3-25 00:14 作者: cavity 時間: 2025-3-25 03:35
https://doi.org/10.1007/978-1-4842-6203-0s based on the formal and mathematical representation of measures. Relying on a knowledge model, we present and evaluate a set of logic-based functionalities able to support novel typologies of comparison of different data cubes.作者: GRUEL 時間: 2025-3-25 10:55 作者: Priapism 時間: 2025-3-25 11:42
Iraj Sadegh Amiri,Mahdi Ariannejad accesses. We show how the simplified functional structure can be exploited by directly integrating the model into the makespan optimization process, reducing complexity by orders of magnitude. Experimental results provide evidence of good prediction quality and successful makespan optimization across a variety of cluster architectures.作者: 歸功于 時間: 2025-3-25 18:14
Optimal Task Ordering in Chain Data Flows: Exploring the Practicality of Non-scalable Solutionsthoroughly discuss the three main directions for exhaustive enumeration of task ordering alternatives, namely backtracking, dynamic programming and topological sorting, and we provide concrete evidence up?to which size and level of flexibility of chain flows they can be applied.作者: Abominate 時間: 2025-3-26 00:03
Exploiting Mathematical Structures of Statistical Measures for Comparison of RDF Data Cubess based on the formal and mathematical representation of measures. Relying on a knowledge model, we present and evaluate a set of logic-based functionalities able to support novel typologies of comparison of different data cubes.作者: 暴發(fā)戶 時間: 2025-3-26 00:14
2,: Shared Distributed Datasets, Storing Shared Data for Multiple and Massive Queries Optimization e. We propose Shared Distributed Datasets (.), a method that dynamically looks for and shares common data among queries. The evaluation shows that, compared to Hive, . consumes on average 20% less memory in the .-scan task and it is 12% faster regarding the execution time of interactive and reporting queries from ..作者: innovation 時間: 2025-3-26 07:07 作者: Apoptosis 時間: 2025-3-26 09:54
A Specimen Case Study for Analysisgraph oriented systems. The advantage of using a unified logical model is that this model remains stable, even though the NoSQL system evolves over time which simplifies the transformation process and saves developers efforts and time.作者: 攤位 時間: 2025-3-26 14:53
https://doi.org/10.1007/978-1-4471-0267-0bust and user parameter-free anytime algorithm and . it employs an instance-based randomized strategy to promote diversity mining. We have applied our method on two real-world large datasets: a marketing dataset and a text dataset. Our results confirm that our method is scalable for large scale sequential data analysis.作者: 慷慨不好 時間: 2025-3-26 19:09
Principles of structured learning,etworks for discovering groups of potentially popular users. Evaluation results show the efficiency and practicality of our solution in conducting complex big data analytics over uncertain and imprecise social networks.作者: GRIEF 時間: 2025-3-26 21:49 作者: ARENA 時間: 2025-3-27 04:53
Service Profiles and Templates,t a scalable buffer, EQM utilizes existing scalable data stores (e.g. HBase) to avoid re-inventing the same elasticity and scalability logic and meanwhile ensures load balancing performance. Experiment results show that stable throughput is achieved at varying data rates using EQM.作者: 神圣不可 時間: 2025-3-27 05:40 作者: EWER 時間: 2025-3-27 12:47
MDA-Based Approach for NoSQL Databases Modellinggraph oriented systems. The advantage of using a unified logical model is that this model remains stable, even though the NoSQL system evolves over time which simplifies the transformation process and saves developers efforts and time.作者: 遍及 時間: 2025-3-27 16:01
MiSeRe-Hadoop: A Large-Scale Robust Sequential Classification Rules Mining Frameworkbust and user parameter-free anytime algorithm and . it employs an instance-based randomized strategy to promote diversity mining. We have applied our method on two real-world large datasets: a marketing dataset and a text dataset. Our results confirm that our method is scalable for large scale sequential data analysis.作者: 值得尊敬 時間: 2025-3-27 19:58 作者: addict 時間: 2025-3-27 22:25
Pre-processing and Indexing Techniques for Constellation Queries in Big Datachniques involve pre-processing the query to reduce its dimensionality as well as indexing the data to fasten stars neighboring computation using a PH-tree. We have implemented our techniques in Spark and evaluated our techniques by a series of experiments. The PH-tree indexing showed very good results and guarantees query answer completeness.作者: compel 時間: 2025-3-28 05:10 作者: 極大痛苦 時間: 2025-3-28 08:23 作者: Defiance 時間: 2025-3-28 11:30
Conference proceedings 2017 Lyon, France, in August 2017..The 24 revised full papers and 11 short papers presented were carefully reviewed and?selected from 97 submissions. The papers are organized in the following topical?sections: new generation data warehouses design; cloud and NoSQL databases; advanced programming paradig作者: Parley 時間: 2025-3-28 17:39
0302-9743 nd Knowledge Discovery, DaWaK 2017, held?in Lyon, France, in August 2017..The 24 revised full papers and 11 short papers presented were carefully reviewed and?selected from 97 submissions. The papers are organized in the following topical?sections: new generation data warehouses design; cloud and No作者: Cocker 時間: 2025-3-28 21:02
Further Case Studies on the People ThemeBaaS users, for obvious legal and competitive reasons. In this paper, we survey the mechanisms that aim at making databases secure in a cloud environment, and discuss current pitfalls and related research challenges.作者: defuse 時間: 2025-3-29 02:29
Enforcing Privacy in Cloud DatabasesBaaS users, for obvious legal and competitive reasons. In this paper, we survey the mechanisms that aim at making databases secure in a cloud environment, and discuss current pitfalls and related research challenges.作者: voluble 時間: 2025-3-29 06:52 作者: 不能強迫我 時間: 2025-3-29 09:59
Conference proceedings 2017ms; non-functional requirements satisfaction; machine learning; social media and twitter analysis; sentiment analysis and user influence; knowledge discovery; ?and data flow management and optimization. ?.作者: PLIC 時間: 2025-3-29 12:14 作者: Vertebra 時間: 2025-3-29 16:15 作者: 字形刻痕 時間: 2025-3-29 21:41
https://doi.org/10.1007/978-1-4842-2382-6h data sources. In the paper, we perform a metric comparison among different methodologies, in order to demonstrate that methodologies classified as hybrid, ontology-based, automatic, and agile are tailored for the Big Data context.作者: 艦旗 時間: 2025-3-30 00:04 作者: TEM 時間: 2025-3-30 04:03
Evaluation of Data Warehouse Design Methodologies in the Context of Big Datah data sources. In the paper, we perform a metric comparison among different methodologies, in order to demonstrate that methodologies classified as hybrid, ontology-based, automatic, and agile are tailored for the Big Data context.作者: FANG 時間: 2025-3-30 09:04 作者: 厚臉皮 時間: 2025-3-30 13:33
