標(biāo)題: Titlebook: Big Data – BigData 2020; 9th International Co Surya Nepal,Wenqi Cao,Liang-Jie Zhang Conference proceedings 2020 Springer Nature Switzerland [打印本頁(yè)] 作者: Intermediary 時(shí)間: 2025-3-21 17:20
書目名稱Big Data – BigData 2020影響因子(影響力)
書目名稱Big Data – BigData 2020影響因子(影響力)學(xué)科排名
書目名稱Big Data – BigData 2020網(wǎng)絡(luò)公開度
書目名稱Big Data – BigData 2020網(wǎng)絡(luò)公開度學(xué)科排名
書目名稱Big Data – BigData 2020被引頻次
書目名稱Big Data – BigData 2020被引頻次學(xué)科排名
書目名稱Big Data – BigData 2020年度引用
書目名稱Big Data – BigData 2020年度引用學(xué)科排名
書目名稱Big Data – BigData 2020讀者反饋
書目名稱Big Data – BigData 2020讀者反饋學(xué)科排名
作者: cacophony 時(shí)間: 2025-3-21 22:51
A Performance Prediction Model for Spark Applicationsmber of configuration parameters that are strongly related to performance. Spark performance, for a given application, can significantly vary because of input data type and size, design & implementation of algorithm, computational resources and parameter configuration. So, involvement of all these v作者: 拉開這車床 時(shí)間: 2025-3-22 02:11
Predicting the DJIA with News Headlines and Historic Data Using Hybrid Genetic Algorithm/Support Vectors. We first examine two state-of-the-art AI techniques, hybrid genetic algorithm/support vector regression and bidirectional encoder representations from transformers (BERT). After that, we proposed a new AI model that uses hybrid genetic algorithm/support vector regression and BERT to predict da作者: 針葉樹 時(shí)間: 2025-3-22 05:53 作者: 休戰(zhàn) 時(shí)間: 2025-3-22 09:07 作者: Dorsal-Kyphosis 時(shí)間: 2025-3-22 16:00 作者: 使高興 時(shí)間: 2025-3-22 20:39
A Web Application for Feral Cat Recognition Through Deep Learningnd detect the number of . feral cats of Australia using deep learning algorithms targeted to data captured from a set of remote sensing cameras. Feral cat recognition is an especially challenging application of deep learning since the cats are often similar and, in some cases, differ only in very sm作者: arthrodesis 時(shí)間: 2025-3-22 23:26 作者: 愛管閑事 時(shí)間: 2025-3-23 02:17 作者: CANDY 時(shí)間: 2025-3-23 06:55
Ensemble Learning for Heterogeneous Missing Data Imputationl and model-based methods. While the former brings bias to the analyses, the latter is usually designed for limited and specific use cases. To overcome the limitations of the two methods, we present a stacked ensemble framework based on the integration of the adaptive random forest algorithm, the Ja作者: progestin 時(shí)間: 2025-3-23 13:38
Validating Goal-Oriented Hypotheses of Business Problems Using Machine Learning: An Exploratory Studf the biggest obstacles is the lack of understanding of how to use data analytics to improve business value. This paper presents ., a method for ensuring that business goals and the corresponding business problems are explicitly traceable to ML projects and where potential (i.e., hypothesized) compl作者: 牽索 時(shí)間: 2025-3-23 17:03
The Collaborative Influence of Multiple Interactions on Successive POI Recommendation the historical behaviors of a user to recommend the top . POIs and rarely consider the current state of the user. Unlike POI recommendation, successive POI recommendation is more sensitive to user preferences and changes in time and space. In order to alleviate the data sparsity, we make full use o作者: exacerbate 時(shí)間: 2025-3-23 18:38 作者: olfction 時(shí)間: 2025-3-23 23:40 作者: 帶傷害 時(shí)間: 2025-3-24 05:53
Cross-Cancer Genome Analysis on?Cancer Classification Using Both Unsupervised and Supervised Approacancer. Through quantifying gene expression levels, next-generation sequencing techniques such as RNA-Seq offer an opportunity for researchers and clinicians to gain a more complete view of a cell’s transcriptome. With the adoption of this new data source, cross-cancer methods for cancer diagnosis ha作者: Counteract 時(shí)間: 2025-3-24 07:49
Heavy Vehicle Classification Through Deep Learningrous hardware and software technologies have been applied to measure traffic volumes by Government agencies and/or organizations such as Google, however they are either expensive to deploy; limited in their ability to disambiguate the kinds of vehicles on the road network, or of increasing importanc作者: albuminuria 時(shí)間: 2025-3-24 11:30 作者: Anonymous 時(shí)間: 2025-3-24 15:36 作者: 死亡率 時(shí)間: 2025-3-24 22:51 作者: Bricklayer 時(shí)間: 2025-3-25 01:28 作者: Chronological 時(shí)間: 2025-3-25 07:21
Springer Series in Materials Sciencember of configuration parameters that are strongly related to performance. Spark performance, for a given application, can significantly vary because of input data type and size, design & implementation of algorithm, computational resources and parameter configuration. So, involvement of all these v作者: jarring 時(shí)間: 2025-3-25 08:10 作者: Curmudgeon 時(shí)間: 2025-3-25 13:07
https://doi.org/10.1007/978-1-4842-8951-8le system, such as an internal or external cloud, a cluster or even distributed public resources (“crowd computing”), needs to be offered with guarantees of predictable performance and utilization cost. Currently, however, this is not possible, because scientific communities lack the technology, bot作者: 衰老 時(shí)間: 2025-3-25 19:27
https://doi.org/10.1007/978-1-4842-8951-8ever, this capability has downsides. Information can be inexact, misleading or indeed downright and deliberately false. . has now entered the common vernacular. In this work, we consider fake news with specific regard to social media. We hypothesise that fake news typically deals with emotive topics作者: insurgent 時(shí)間: 2025-3-25 22:54
Surgical Treatments: Lunate Excisionionally, genetic variation analyses have been based on the human reference genome assembled from a relatively small human population. However, genetic variation could be discovered more comprehensively by using a collection of genomes i.e., pan-genome as a reference. The pan-genomic references can b作者: CRUE 時(shí)間: 2025-3-26 02:53 作者: TAP 時(shí)間: 2025-3-26 05:27 作者: Brocas-Area 時(shí)間: 2025-3-26 11:37 作者: 隱士 時(shí)間: 2025-3-26 15:44 作者: Brittle 時(shí)間: 2025-3-26 16:47 作者: Enervate 時(shí)間: 2025-3-26 23:27
Surgical Treatments: Radial Osteotomy the historical behaviors of a user to recommend the top . POIs and rarely consider the current state of the user. Unlike POI recommendation, successive POI recommendation is more sensitive to user preferences and changes in time and space. In order to alleviate the data sparsity, we make full use o作者: restrain 時(shí)間: 2025-3-27 04:11
Analysis of Dynamic Forces in Machinery,for each successful compound. The developers need to efficiently discover initial candidates before actual synthesis, optimization and evaluation. We developed a similarity-based chemical XAI system to discover probable compounds’ spaces based on mixture of multiple mutated exemplars and bioassay ex作者: GEAR 時(shí)間: 2025-3-27 06:42
The Free Calculus and the Elementary Ideals,cal trials for more than four decades. Managing information from clinical trials and published results in the Big Data era presents new challenges and opportunities. These include and are not limited to data attribution, aggregation, adaptability, and prompt analysis. Hence, the Center has created a作者: IRK 時(shí)間: 2025-3-27 10:55 作者: PAD416 時(shí)間: 2025-3-27 15:48
Civil Law and Civil Procedural Law,rous hardware and software technologies have been applied to measure traffic volumes by Government agencies and/or organizations such as Google, however they are either expensive to deploy; limited in their ability to disambiguate the kinds of vehicles on the road network, or of increasing importanc作者: Peristalsis 時(shí)間: 2025-3-27 21:21 作者: 排斥 時(shí)間: 2025-3-27 23:15
0302-9743 ations and Analytics, Big Data in Enterprise Management Models and Practices, Big Data in Government Management Models and Practices, and Big Data in Smart Planet Solutions...?.978-3-030-59611-8978-3-030-59612-5Series ISSN 0302-9743 Series E-ISSN 1611-3349 作者: metropolitan 時(shí)間: 2025-3-28 02:59 作者: Comedienne 時(shí)間: 2025-3-28 07:47
Surgical Treatments: Lunate Excisionexing pan-genomes and assembling a reference genome from the pan-genomic index. We experimentally show the scalability of the PanGenSpark with human pan-genomes in a distributed Spark cluster comprising 448 cores distributed to 26 computing nodes. Assembling a consensus genome of a pan-genome includ作者: Alienated 時(shí)間: 2025-3-28 11:52 作者: Project 時(shí)間: 2025-3-28 15:52
Introduction to Kienb?ck’s Diseasehastic passengers’ destination distribution based on the observation that the distribution has obvious periodicity and randomicity. We validate our method based on extensive experiments, using AFC data and weather data in Shenzhen, China over two years. The evaluation results show that our approach 作者: 后天習(xí)得 時(shí)間: 2025-3-28 21:17 作者: 名義上 時(shí)間: 2025-3-29 00:08 作者: 河潭 時(shí)間: 2025-3-29 05:31 作者: 鉗子 時(shí)間: 2025-3-29 07:32 作者: entrance 時(shí)間: 2025-3-29 14:36
The Free Calculus and the Elementary Ideals, friendly interface to consult aggregated information promptly. This work establishes a Semantic Data Model for each clinical trial to create a summary of key information in a machine-readable format, and to enrich each summary with semantic information. In addition, it allows the union of these mod作者: bromide 時(shí)間: 2025-3-29 17:25
Richard H. Crowell,Ralph H. Foxstatus from tissue sample gene expressions. We use genes selected based on the prior mutual information technique. First, we select the top 500 genes from candidate genes without considerations for overlap in the predictability of those genes. We then applied Recursive Feature Elimination (RFE) to s作者: 凝結(jié)劑 時(shí)間: 2025-3-29 19:51
Civil Law and Civil Procedural Law,ction of travel. We apply and compare leading deep learning approaches including You Only Look Once version 3 (YOLOv3) and Single Shot Multi-Box Detector (SSD). This paper builds upon earlier work [.] which focused on data (video) from a single traffic junction in Melbourne. This work is based on a 作者: 變形 時(shí)間: 2025-3-30 00:35 作者: 哺乳動(dòng)物 時(shí)間: 2025-3-30 04:06
Scalable Reference Genome Assembly from Compressed Pan-Genome Index with Sparkexing pan-genomes and assembling a reference genome from the pan-genomic index. We experimentally show the scalability of the PanGenSpark with human pan-genomes in a distributed Spark cluster comprising 448 cores distributed to 26 computing nodes. Assembling a consensus genome of a pan-genome includ作者: choleretic 時(shí)間: 2025-3-30 10:51
A Web Application for Feral Cat Recognition Through Deep Learninghe basis for the web application. Using images of cats from cameras in five different forests around Victoria, we achieved an average accuracy of identification of individual (distinct) cats of 89.4% with a maximum accuracy of 96.3%. This work is used to support ecologists in the School of Bioscienc作者: 粗野 時(shí)間: 2025-3-30 13:38 作者: HAIRY 時(shí)間: 2025-3-30 19:10
Ensemble Learning for Heterogeneous Missing Data Imputationets that contained labelled and unlabelled data. The experiments showed that our framework produces encouraging and competitive results when compared to statistical and model-based methods. Since the framework works for various datasets, it overcomes the model-based limitations that were found in th作者: ODIUM 時(shí)間: 2025-3-30 21:15 作者: anthesis 時(shí)間: 2025-3-31 01:24 作者: interior 時(shí)間: 2025-3-31 07:42
Chemical XAI to Discover Probable Compounds’ Spaces Based on Mixture of Multiple Mutated Exemplars armation of biological activity and target obtained from public DB or literature including related specific text string. The basis of prediction is explainable by showing biological activity and target of similar compounds included in the extracted spaces. The mixture of multiple mutated exemplars an作者: 兇猛 時(shí)間: 2025-3-31 10:14
Clinical Trials Data Management in the Big Data Era friendly interface to consult aggregated information promptly. This work establishes a Semantic Data Model for each clinical trial to create a summary of key information in a machine-readable format, and to enrich each summary with semantic information. In addition, it allows the union of these mod作者: overture 時(shí)間: 2025-3-31 14:21 作者: 平常 時(shí)間: 2025-3-31 18:25
Heavy Vehicle Classification Through Deep Learningction of travel. We apply and compare leading deep learning approaches including You Only Look Once version 3 (YOLOv3) and Single Shot Multi-Box Detector (SSD). This paper builds upon earlier work [.] which focused on data (video) from a single traffic junction in Melbourne. This work is based on a 作者: 殘暴 時(shí)間: 2025-4-1 00:02
Introduction to Kienb?ck’s Diseaseat MCF outperforms better than traditional cuckoo filter on false positive in theory. Experiments demonstrate that the query time of MCF grows linearly with the growth of number of cuckoo filters, decreases gradually with the growth of sliding window number, and increases with the growth of total elements.作者: 領(lǐng)帶 時(shí)間: 2025-4-1 03:44
