標(biāo)題: Titlebook: Big Data Analytics; 4th International Co Naveen Kumar,Vasudha Bhatnagar Conference proceedings 2015 Springer International Publishing Switz [打印本頁] 作者: 文化修養(yǎng) 時間: 2025-3-21 16:09
書目名稱Big Data Analytics影響因子(影響力)
書目名稱Big Data Analytics影響因子(影響力)學(xué)科排名
書目名稱Big Data Analytics網(wǎng)絡(luò)公開度
書目名稱Big Data Analytics網(wǎng)絡(luò)公開度學(xué)科排名
書目名稱Big Data Analytics被引頻次
書目名稱Big Data Analytics被引頻次學(xué)科排名
書目名稱Big Data Analytics年度引用
書目名稱Big Data Analytics年度引用學(xué)科排名
書目名稱Big Data Analytics讀者反饋
書目名稱Big Data Analytics讀者反饋學(xué)科排名
作者: 使入迷 時間: 2025-3-21 22:57
A Framework to Harvest Page Views of Web for Banner Advertisingg the clusters of similar websites. Rather than managing a single website, the publisher manages the aggregated advertising space of a collection of websites. As a result, the advertisement space could be expanded significantly and it will provide the opportunity for increased number of publishers t作者: Fretful 時間: 2025-3-22 00:51
Utility-Based Control Flow Discovery from Business Process Event Logstical (based on frequency) and semantic (based on user’s objective) aspects while driving a process model. We conduct experiments on real-world dataset and synthetic dataset to demonstrate the effectiveness of our approach.作者: Creditee 時間: 2025-3-22 08:03 作者: gruelling 時間: 2025-3-22 11:31 作者: relieve 時間: 2025-3-22 15:20
VDMR-DBSCAN: Varied Density MapReduce DBSCANDBSCAN is applied on each DLS using its corresponding density parameters. Most importantly, we propose a novel merging technique, which merges the similar density clusters present in different partitions and produces meaningful and compact clusters of varied density. We experimented on large and sma作者: 令人悲傷 時間: 2025-3-22 19:55 作者: noxious 時間: 2025-3-22 22:02
Khanan: Performance Comparison and Programming ,-Miner Algorithm in Column-Oriented and Relational Dgorithm is one of the first and most widely used Process Discovery techniques. Our objective is to investigate which of the databases (Relational or NoSQL) performs better for a Process Discovery application under Process Mining. We implement the .-miner algorithm on relational (row-oriented) and No作者: 束以馬具 時間: 2025-3-23 03:44
A New Proposed Feature Subset Selection Algorithm Based on Maximization of Gain Ratioain. A unified metric, which combines all three parameters (number of features, runtime, classification accuracy) together, has also been taken to compare the algorithms. The result shows that our Proposed algorithm has a significant improvement than other feature selection algorithms for large dime作者: SOBER 時間: 2025-3-23 09:29 作者: 減弱不好 時間: 2025-3-23 12:26 作者: 吸引力 時間: 2025-3-23 17:25 作者: Bereavement 時間: 2025-3-23 18:14
https://doi.org/10.1007/978-3-662-67377-5tical (based on frequency) and semantic (based on user’s objective) aspects while driving a process model. We conduct experiments on real-world dataset and synthetic dataset to demonstrate the effectiveness of our approach.作者: CODA 時間: 2025-3-24 01:19 作者: ANA 時間: 2025-3-24 06:04 作者: nostrum 時間: 2025-3-24 09:48 作者: 優(yōu)雅 時間: 2025-3-24 10:43 作者: 大猩猩 時間: 2025-3-24 15:57
,El Ni?o Southern Oscillation connection,gorithm is one of the first and most widely used Process Discovery techniques. Our objective is to investigate which of the databases (Relational or NoSQL) performs better for a Process Discovery application under Process Mining. We implement the .-miner algorithm on relational (row-oriented) and No作者: pantomime 時間: 2025-3-24 22:21
https://doi.org/10.1007/b138817ain. A unified metric, which combines all three parameters (number of features, runtime, classification accuracy) together, has also been taken to compare the algorithms. The result shows that our Proposed algorithm has a significant improvement than other feature selection algorithms for large dime作者: Flawless 時間: 2025-3-25 02:05
Heritable Variation in Populations,ion data is used to determine the most appropriate approved drug for the cancer type. Additionally, suitable clinical trial information will be retrieved based on the patient’s geographicals location and phenotype. We then integrate the genomic marker and clinical data of the patient which paves the作者: 吊胃口 時間: 2025-3-25 06:32 作者: 牽索 時間: 2025-3-25 10:22
Genomics 3.0: Big-data in Precision Medicineoaches with all the constituent parts integrated into a single system through complex meta-analysis. Finally, we present two big-data platforms . and .. iOMICS platform is deployed at Google cloud for translational genomics; whereas, DiscoverX is deployed at Amazon Web Services for precision medicine.作者: engrossed 時間: 2025-3-25 14:34 作者: 收養(yǎng) 時間: 2025-3-25 17:30
Intrapreneurship-Programme in der Praxisplore e-commerce databases. We identify five limitations in the query and result panel that deter exploratory search using faceted browsing. We propose nine add-on extensions—four in the query panel and five in the result panel—to address these limitations.作者: 匍匐 時間: 2025-3-25 21:01
Intrapreneurship-Potenziale bei Mitarbeitern for efficiently mining high-utility itemsets. We conduct extensive experiments on real and synthetic datasets and our results show that our proposed algorithm outperforms the state-of-the-art algorithms in terms of total execution time and number of itemsets that need to be explored.作者: 傳染 時間: 2025-3-26 00:49
Open Source Social Media Analytics for Intelligence and Security Informatics Applicationsof the paper is on mining free-form textual content present in social media websites. In particular we describe two important application: online radicalization and civil unrest. In addition to covering basic concepts and applications, we discuss open research problem, important papers, publication venues, research results and future directions.作者: NOMAD 時間: 2025-3-26 04:42
Information Exploration in E-Commerce Databasesplore e-commerce databases. We identify five limitations in the query and result panel that deter exploratory search using faceted browsing. We propose nine add-on extensions—four in the query panel and five in the result panel—to address these limitations.作者: 繁榮地區(qū) 時間: 2025-3-26 10:45 作者: gustation 時間: 2025-3-26 13:36
0302-9743 aAnalytics, BDA 2015, held in Hyderabad, India, in December 2015. ..The 9 revised full papers and 9invited papers were carefully reviewed and selected from 61 submissions andcover topics on big data: security and privacy; big data in commerce; big data:models and algorithms; and big data in medicine作者: 說不出 時間: 2025-3-26 20:15
Mobility Big Data Analysis and Visualization (Invited Talk)d data and vehicle recorder data, and developed platforms for processing, analyzing, and visualizing them. In this paper I briefly introduce our analysis and visualization of passenger flows in public transportation systems and behaviors of vehicle drivers.作者: osteocytes 時間: 2025-3-27 00:19 作者: 斗爭 時間: 2025-3-27 02:28 作者: 名義上 時間: 2025-3-27 07:54
Conference proceedings 2015dia, in December 2015. ..The 9 revised full papers and 9invited papers were carefully reviewed and selected from 61 submissions andcover topics on big data: security and privacy; big data in commerce; big data:models and algorithms; and big data in medicine..作者: 魅力 時間: 2025-3-27 10:57
Privacy Protection or Data Value: Can We Have Both?of data exploitation will not be sustainable either due to customer dissatisfaction or government intervention to ensure private information is treated with the same level of protection that we currently find in paper-based systems. Legal, technical, and moral boundaries need to be placed on how per作者: esthetician 時間: 2025-3-27 16:11
Open Source Social Media Analytics for Intelligence and Security Informatics Applicationsedia intelligence is a sub-field within OSINT with a focus on extracting insights from publicly available data in Web 2.0 platforms like Twitter (micro-blogging website), YouTube (video-sharing website) and Facebook (social-networking website). In this paper, we present an overview of Intelligence a作者: Atheroma 時間: 2025-3-27 17:53 作者: photophobia 時間: 2025-3-28 00:04 作者: 拋媚眼 時間: 2025-3-28 03:58
Utility-Based Control Flow Discovery from Business Process Event Logsrted business processes. Fuzzy-Miner (FM) is a popular algorithm within Process Mining which consists of discovering a process model from the event-logs. In traditional FM algorithm, the extracted process model consists of nodes and edges of equal value (in terms of the economic utility and objectiv作者: forestry 時間: 2025-3-28 09:02 作者: iodides 時間: 2025-3-28 13:35
Design of Algorithms for Big Data Analyticsr asynchronous and simultaneous processing of smaller chunks of large datasets. The Map-Reduce paradigm provides a very effective mechanism for designing efficient algorithms for processing high volume datasets. Sometimes a simple adaptation of a sequential solution of a problem to design Map-Reduce作者: 火車車輪 時間: 2025-3-28 18:09 作者: 起皺紋 時間: 2025-3-28 20:50 作者: helper-T-cells 時間: 2025-3-29 02:14
VDMR-DBSCAN: Varied Density MapReduce DBSCANsuffers from major drawbacks like high computational cost, inability to find varied density clusters and dependency on user provided input density parameters. To address these issues, we propose a novel density based clustering algorithm titled, VDMR-DBSCAN (Varied Density MapReduce DBSCAN), a scala作者: 高原 時間: 2025-3-29 05:08
Concept Discovery from Un-Constrained Distributed Context concepts that describe special kind of relationships between set of attributes and set of objects. These concepts are related to each other and are arranged in a hierarchy. FCA finds its application in several areas including data mining, machine learning and semantic web..Few iterative MapReduce b作者: CERE 時間: 2025-3-29 09:32 作者: 的’ 時間: 2025-3-29 13:24 作者: 朋黨派系 時間: 2025-3-29 18:16
Genomics 3.0: Big-data in Precision Medicinecience and technology of big-data translational genomics and precision medicine - we present various components of this complex . science. We also identify diverse idiosyncrasies of big-data with respect to application of computer algorithms and mathematics in genomics. We discuss the 7Vs of big-dat作者: Tidious 時間: 2025-3-29 23:06 作者: hurricane 時間: 2025-3-30 02:19
Conference proceedings 2015dia, in December 2015. ..The 9 revised full papers and 9invited papers were carefully reviewed and selected from 61 submissions andcover topics on big data: security and privacy; big data in commerce; big data:models and algorithms; and big data in medicine..作者: enchant 時間: 2025-3-30 07:33
https://doi.org/10.1007/978-3-319-27057-9Algorithms; Big data; Data analytics; Data mining; Databases; Decision support systems; E-commerce; Enterpr作者: 其他 時間: 2025-3-30 08:42
978-3-319-27056-2Springer International Publishing Switzerland 2015作者: 神經(jīng) 時間: 2025-3-30 14:56
Raysa Geaquinto Rocha,Jo?o Leit?oof data exploitation will not be sustainable either due to customer dissatisfaction or government intervention to ensure private information is treated with the same level of protection that we currently find in paper-based systems. Legal, technical, and moral boundaries need to be placed on how per作者: absolve 時間: 2025-3-30 20:33 作者: 平常 時間: 2025-3-30 21:46
Intrapreneurship-Programme in der Praxis is contained in their database or lack technical expertise to form proper queries. Faceted navigation is a central tool that these e-commerce sites use to address this challenge. A typical faceted interface has two main component panels: a query panel and a result panel. Faceted browsing is primari作者: Flu表流動 時間: 2025-3-31 02:38
Leitfaden für die praktische Umsetzungconomy. It is a major source of revenue for the major search engine and social networking sites. Search engine, context-specific and banner advertising are the major modes of online advertising. The banner advertisement mode has certain advantages over other modes of advertising. Currently, the numb作者: febrile 時間: 2025-3-31 05:46
