標(biāo)題: Titlebook: Big Data Analytics and Knowledge Discovery; 21st International C Carlos Ordonez,Il-Yeol Song,Ismail Khalil Conference proceedings 2019 Spri [打印本頁(yè)] 作者: 贖罪 時(shí)間: 2025-3-21 18:37
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(kāi)度
書目名稱Big Data Analytics and Knowledge Discovery網(wǎng)絡(luò)公開(kāi)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: amphibian 時(shí)間: 2025-3-21 23:41 作者: 觀點(diǎn) 時(shí)間: 2025-3-22 00:48 作者: Compassionate 時(shí)間: 2025-3-22 04:50 作者: 間諜活動(dòng) 時(shí)間: 2025-3-22 10:30
Mining Sequential Patterns of Historical Purchases for E-commerce Recommendationin its user-item matrix input, to make it more informative before collaborative filtering. Existing recommendation systems that attempt to use mining and some sequences are those referred to as LiuRec09, ChoiRec12, SuChenRec15, and HPCRec18. These systems use mining based techniques of clustering, f作者: attenuate 時(shí)間: 2025-3-22 15:43
Discovering and Visualizing Efficient Patterns in Cost/Utility Sequencesta. In sequential pattern mining, patterns are selected based on criteria such as the occurrence frequency, periodicity, or utility (eg. profit). Although this has many applications, it does not consider the effort or resources consumed to apply these patterns. To address this issue, this paper prop作者: circumvent 時(shí)間: 2025-3-22 17:19
Efficient Row Pattern Matching Using Pattern Hierarchies for Sequence OLAPtransition pattern ., movement pattern .) on sequence data and executes multi-dimensional aggregate using . (such as . and .) and . (such as . and .). The pattern OLAP operations are specific to Sequence OLAP and involve a hierarchy of multiple patterns. When sequence data is stored in relational da作者: 厚顏無(wú)恥 時(shí)間: 2025-3-22 23:09
Statistically Significant Discriminative Patterns Searchingiginal enumeration strategy of the patterns, which allows to exploit some degrees of anti-monotonicity on the measures of discriminance and statistical significance. Experimental results demonstrate that the performance of the SSDPS algorithm is better than others. In addition, the number of generat作者: Audiometry 時(shí)間: 2025-3-23 03:01 作者: Statins 時(shí)間: 2025-3-23 07:54
RDFPartSuite: Bridging Physical and Logical RDF Partitioningexibility motivated the use of this standard in other domains and today RDF datasets are big sources of information. In this line, the research on scalable distributed and parallel RDF processing systems has gained momentum. Most of these systems apply partitioning algorithms that use the triple, th作者: 作繭自縛 時(shí)間: 2025-3-23 11:19 作者: 受辱 時(shí)間: 2025-3-23 17:23
Democratization of OLAP DSMSing data and exposed the need for every organization to exploit it. This paper reviews the evolution of Data Stream Management Systems (DSMS) and the convergence into Online Analytical Processing (OLAP) DSMS. The discussion is focused on three current solutions: Scuba, Apache Druid, and Apache Pinot作者: NUL 時(shí)間: 2025-3-23 19:29
Leveraging the Data Lake: Current State and Challenges exploit these complex data for competitive advantages, the data lake recently emerged as a concept for more flexible and powerful data analytics. However, existing literature on data lakes is rather vague and incomplete, and the various realization approaches that have been proposed neither cover a作者: Decrepit 時(shí)間: 2025-3-23 22:45
SDWP: A New Data Placement Strategy for Distributed Big Data Warehouses in Hadoopnd guiding the physical design of a data warehouse. In big data warehouses, the most expensive operation of an OLAP query is the star join, which requires many Spark stages. In this paper, we propose a new data placement strategy in the Apache Hadoop environment called “Smart Data Warehouse Placemen作者: 冬眠 時(shí)間: 2025-3-24 03:54
Improved Programming-Language Independent MapReduce on Shared-Memory Systemsa sets. However, modern data processing runtimes, implementing the MapReduce programming paradigm, do not generally support the use of arbitrary programming languages. Access to programming-language independent data processing can offer great value to organizations as it enables leveraging existing 作者: Dedication 時(shí)間: 2025-3-24 08:13 作者: Crohns-disease 時(shí)間: 2025-3-24 10:46
https://doi.org/10.1007/978-1-4842-9234-1tomatically assessed with a statistical . test. Experimental results, on both synthetic and real-life data, show that our method is more suitable for sensor interval streams and provides more precise information in comparison with existing approaches.作者: 音樂(lè)學(xué)者 時(shí)間: 2025-3-24 17:30
https://doi.org/10.1007/978-1-4842-9234-1lakes, such as governance or data models. Based on these insights, we identify challenges and research gaps concerning (1)?data lake architecture, (2) data lake governance, and (3) a comprehensive strategy to realize data lakes. These challenges still need to be addressed to successfully leverage the data lake in practice.作者: 廣告 時(shí)間: 2025-3-24 20:39 作者: Anticoagulants 時(shí)間: 2025-3-25 02:45
Detecting the Onset of Machine Failure Using Anomaly Detection Methodsresults show that the majority of the tested algorithms can achieve a F1-score of more than 0.9. Successfully detecting failures as they begin to occur promises to address key issues in maintenance like safety and cost effectiveness.作者: 積習(xí)難改 時(shí)間: 2025-3-25 03:46 作者: Regurgitation 時(shí)間: 2025-3-25 09:15 作者: 豐滿中國(guó) 時(shí)間: 2025-3-25 12:54 作者: Gobble 時(shí)間: 2025-3-25 16:04 作者: 發(fā)誓放棄 時(shí)間: 2025-3-25 20:13
Gianluca Baldassarre,Marco Mirollita sources; its goal is to verify the feasibility and the usefulness of a data integration process that supports situ-specific and large-scale analyses made available by integrating information at different levels of detail.作者: Bureaucracy 時(shí)間: 2025-3-26 01:02 作者: Cardiac 時(shí)間: 2025-3-26 07:02
https://doi.org/10.1007/978-1-4842-9234-1convergence into Online Analytical Processing (OLAP) DSMS. The discussion is focused on three current solutions: Scuba, Apache Druid, and Apache Pinot in use in large production environments that satisfy the real-time OLAP on streaming data. Finally, a discussion is presented on a potential evolution of OLAP DSMS and open problems.作者: falsehood 時(shí)間: 2025-3-26 12:24 作者: Flat-Feet 時(shí)間: 2025-3-26 16:32 作者: 現(xiàn)暈光 時(shí)間: 2025-3-26 20:02
Democratization of OLAP DSMSconvergence into Online Analytical Processing (OLAP) DSMS. The discussion is focused on three current solutions: Scuba, Apache Druid, and Apache Pinot in use in large production environments that satisfy the real-time OLAP on streaming data. Finally, a discussion is presented on a potential evolution of OLAP DSMS and open problems.作者: 安定 時(shí)間: 2025-3-26 23:36
Introducing .NET for Apache Spark. We introduce a number of current optimizations and extensions to the state-of-the-art. Furthermore, this paper presents the first comparative benchmark between XRT and many popular MapReduce runtimes in order to highlight the performance capabilities of programming-language independent data processing.作者: 叫喊 時(shí)間: 2025-3-27 02:48
Improved Programming-Language Independent MapReduce on Shared-Memory Systems. We introduce a number of current optimizations and extensions to the state-of-the-art. Furthermore, this paper presents the first comparative benchmark between XRT and many popular MapReduce runtimes in order to highlight the performance capabilities of programming-language independent data processing.作者: observatory 時(shí)間: 2025-3-27 09:18 作者: 罵人有污點(diǎn) 時(shí)間: 2025-3-27 10:06 作者: radiograph 時(shí)間: 2025-3-27 15:43
Gianluca Baldassarre,Marco Mirolliroach to anomaly detection for early detection of faults for a condition-based maintenance. For the purpose of this study, a belt-driven single degree of freedom robot arm is designed. The robot arm is conditioned on the torque required to move the arm forward and backward, simulating a door opening作者: Statins 時(shí)間: 2025-3-27 20:51 作者: 吸引力 時(shí)間: 2025-3-27 23:05
,Schalenf?rmige Hybridverbunde und Inserts,ch, which in turn has led to .. In urban research, researchers who conduct paper-based or telephone-based travel surveys often collect biased and inaccurate data about movements of their participants. Although the use of global positioning system (GPS) trackers in travel studies improves the accurac作者: 下級(jí) 時(shí)間: 2025-3-28 02:57
https://doi.org/10.1007/978-3-662-68075-9costly. How can we quickly discover all the frequent items that are favored individually by at least a given number of users? This new problem not only has strong connections with several well-known problems, such as the frequent item mining problem, it also finds applications in fields such as spon作者: 領(lǐng)袖氣質(zhì) 時(shí)間: 2025-3-28 06:59
https://doi.org/10.1007/978-1-4302-2456-3in its user-item matrix input, to make it more informative before collaborative filtering. Existing recommendation systems that attempt to use mining and some sequences are those referred to as LiuRec09, ChoiRec12, SuChenRec15, and HPCRec18. These systems use mining based techniques of clustering, f作者: Canvas 時(shí)間: 2025-3-28 13:41
Windows Communication Foundation,ta. In sequential pattern mining, patterns are selected based on criteria such as the occurrence frequency, periodicity, or utility (eg. profit). Although this has many applications, it does not consider the effort or resources consumed to apply these patterns. To address this issue, this paper prop作者: genuine 時(shí)間: 2025-3-28 17:33 作者: 中子 時(shí)間: 2025-3-28 19:46
https://doi.org/10.1007/978-1-4302-4333-5iginal enumeration strategy of the patterns, which allows to exploit some degrees of anti-monotonicity on the measures of discriminance and statistical significance. Experimental results demonstrate that the performance of the SSDPS algorithm is better than others. In addition, the number of generat作者: 蒸發(fā) 時(shí)間: 2025-3-29 01:48 作者: ostrish 時(shí)間: 2025-3-29 06:22
https://doi.org/10.1007/978-1-4842-9234-1exibility motivated the use of this standard in other domains and today RDF datasets are big sources of information. In this line, the research on scalable distributed and parallel RDF processing systems has gained momentum. Most of these systems apply partitioning algorithms that use the triple, th作者: 頌揚(yáng)國(guó)家 時(shí)間: 2025-3-29 08:15
https://doi.org/10.1007/978-1-4842-9234-1ority of existing approaches deals with such data as time point events to find . relations that induces loss of information when dealing with events lasting in time, i.e intervals. Other interval-based approaches focus on qualitative patterns and are sensitive to temporal variability. We consider th作者: discord 時(shí)間: 2025-3-29 15:18
https://doi.org/10.1007/978-1-4842-9234-1ing data and exposed the need for every organization to exploit it. This paper reviews the evolution of Data Stream Management Systems (DSMS) and the convergence into Online Analytical Processing (OLAP) DSMS. The discussion is focused on three current solutions: Scuba, Apache Druid, and Apache Pinot作者: Corroborate 時(shí)間: 2025-3-29 16:39
https://doi.org/10.1007/978-1-4842-9234-1 exploit these complex data for competitive advantages, the data lake recently emerged as a concept for more flexible and powerful data analytics. However, existing literature on data lakes is rather vague and incomplete, and the various realization approaches that have been proposed neither cover a作者: 著名 時(shí)間: 2025-3-29 20:09
https://doi.org/10.1007/978-1-4842-9234-1nd guiding the physical design of a data warehouse. In big data warehouses, the most expensive operation of an OLAP query is the star join, which requires many Spark stages. In this paper, we propose a new data placement strategy in the Apache Hadoop environment called “Smart Data Warehouse Placemen作者: Anticoagulants 時(shí)間: 2025-3-30 02:02 作者: Assault 時(shí)間: 2025-3-30 05:42
Lecture Notes in Computer Sciencehttp://image.papertrans.cn/b/image/185605.jpg作者: Melanoma 時(shí)間: 2025-3-30 09:34 作者: Pseudoephedrine 時(shí)間: 2025-3-30 15:38
Big Data Analytics and Knowledge Discovery978-3-030-27520-4Series ISSN 0302-9743 Series E-ISSN 1611-3349 作者: Cardioversion 時(shí)間: 2025-3-30 18:57
https://doi.org/10.1007/978-3-030-27520-4artificial intelligence; big data; big datum; cloud computing; computer systems; data management; data min作者: innovation 時(shí)間: 2025-3-30 21:37 作者: colony 時(shí)間: 2025-3-31 02:20 作者: 證明無(wú)罪 時(shí)間: 2025-3-31 07:36
https://doi.org/10.1007/978-3-662-68075-9s the number of users needed to probe to .—regardless of the number of users—as long as slight inaccuracy in the output is permitted. For reasonably sized input, our algorithm needs to probe only . of the users, whereas the naive approach needs to probe all of them.作者: 決定性 時(shí)間: 2025-3-31 11:24
https://doi.org/10.1007/978-1-4302-2456-3ntial pattern of customer clicks and purchases to capture better customer behavior. This paper proposes an algorithm called HSPRec (Historical Sequential Pattern Recommendation System), which mines frequent sequential click and purchase patterns for enriching the (i) user-item matrix quantitatively,
