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检索条件"任意字段=2nd International Conference on Algorithms for Big Data, ICABD 2014"

共 223 条记录，以下是151-160 订阅

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ACM international conference Proceeding Series

ACM International Conference Proceeding Series

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2nd international conference on Medical and Health Informatics, ICMHI 2018

ISBN: (纸本)9781450363891

The proceedings contain 43 papers. The topics discussed include: understanding of users' response to the intervention of FDA's new deeming rules in Twitter;decision analysis of brain arteriovenous malformation treatment;risk factors of neonatal mortality incidence in Muna Regency in 2014;drug adherence with hypertension status at the Bajoe community health centre of Bone Regency in 2016;survival analysis of chronic renal failure patients undergoing hemodialysis at hospital in Makassar within 2012-2015;treatment response analysis in patients with multidrug resistant tuberculosis (MDR TB) at Labuang Baji public hospital in Makassar city;kidney disease with metabolic syndrome risk factor using dynamic model approach in Indonesia;use of group-based trajectory modeling to explore patterns of stroke in different gender groups;disease trajectory visualization system based on big data analytics;the epidemiology and cost of hospital-treated traumatic brain injuries: a 10-year nation-wide survey in Taiwan;retrieving and clustering keywords in neurosurgery operation reports using text mining techniques;strengthening community attributes in the open-clinic GA open source collaboration: an analysis of prevailing practices and thoughts from internet blogs;towards automated knowledge discovery of hepatocellular carcinoma: extract patient information from Chinese clinical reports;an embedding-based approach for oral disease diagnosis prediction from electronic medical records;enhanced chaotic map-based authenticated key agreement with privacy protection for multi-receiver environment;interactive augmented live virtual reality streaming: a health care application;and an intelligent flexbar for upper-limb rehabilitation based on wireless sensor network.

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Proceedings of the 2016 2nd international conference on Contemporary Computing and Informatics, IC3I 2016

Proceedings of the 2016 2nd International Conference on Cont...

引用

2nd international conference on Contemporary Computing and Informatics, IC3I 2016

ISBN: (纸本)9781509052554

The proceedings contain 160 papers. The topics discussed include: a novel data mining approach for brain tumour detection;educational intelligence: applying cloud-based big data analytics to the Indian education sector;comparison of FOSS based profiling tools in Linux operating system environment;comparison of back propagation training algorithms for software defect prediction;fine tuning the parameters of back propagation algorithm for optimum learning performance;rough-set and artificial neural networks based image classification;a self-monitoring online sequential learning mechanism for feedfoward neural networks;a review of the application of data mining techniques for decision making in agriculture;autonomous walking stick for the blind using echolocation and image processing;consumer preferences of information search channel and the role of information technology;building secure healthcare services using OAuth 2.0 and JSON web token in IOT cloud scenario;Openstack- paradigm shift to open source cloud computing & its integration;lean Six Sigma approach for global supply chain management using Industry 4.0 and IIoT;efficient tag based personalised collaborative movie reccommendation system;and locate, promote and split: an exponentially fast localization algorithm for wireless sensor networks.

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Towards clustering validation in big data context 17

Towards clustering validation in big data context

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2nd international conference on big data Cloud and Applications, BDCA 2017

作者： Zerabi, Soumeya Meshoul, Souham Merniz, Amina Melal, Radia Computer Science and Application Department Abdelhamid Mehri Constantine 2 University Ali Mendjeli Constantine Algeria

ISBN: (纸本)9781450348522

Clustering1is an essential task in many areas such as machine learning, data mining and computer vision among others. Cluster validation aims to assess the quality of partitions obtained by clustering algorithms. Several indexes have been developed for cluster validation purpose. They can be external or internal depending on the availability of ground truth clustering. This paper deals with the issue of cluster validation of large data set. Indeed, in the era of big data this task becomes even more difficult to handle and requires parallel and distributed approaches. In this work, we are interested in external validation indexes. More specifically, this paper proposes a model for purity based cluster validation in parallel and distributed manner using Map-Reduce paradigm in order to be able to scale with increasing dataset sizes. The experimental results show that our proposed model is valid and achieves properly cluster validation of large datasets. © 2017 Association for Computing Machinery.

关键词： Clustering algorithms

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2nd international Workshop on Algorithmic Aspects of Cloud Computing, ALGOCLOUD 2016

2nd International Workshop on Algorithmic Aspects of Cloud C...

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2nd international Workshop on Algorithmic Aspects of Cloud Computing, ALGOCLOUD 2016

ISBN: (纸本)9783319570440

The proceedings contain 11 papers. The special focus in this conference is on Algorithmic Aspects of Cloud Computing. The topics include: Efficient indexing on top of NoSQL databases;an apache spark implementation for sentiment analysis on twitter data;a cloud-based time-dependent routing service;a big data architecture for traffic forecasting using multi-source information;mining uncertain graphs;recovering from cloud application deployment failures through re-execution;fair, fast and frugal large scale matchmaking for VM placement;survey of machine learning algorithms on spark over DHT-based structures;scaling out to become doctrinal;a survey on big data and collective intelligence.

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Telecom big data for urban transport analysis – a case study of split-dalmatia county in Croatia 2

Telecom big data for urban transport analysis – a case stud...

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2nd international conference on Smart data and Smart Cities, UDMS 2017

作者： Baučić, M. Jajac, N. Bućan, M. Faculty of Civil Engineering Architecture and Geodesy University of Split Matice hrvatske 15 Split21000 Croatia Split-Dalmatia County Domovinskog rata 2 Split21 000 Croatia

Today, big data has become widely available and the new technologies are being developed for big data storage architecture and big data analytics. An ongoing challenge is how to incorporate big data into GIS applications supporting the various domains. international Transport Forum explains how the arrival of big data and real-time data, together with new data processing algorithms lead to new insights and operational improvements of transport. Based on the telecom customer data, the Study of Tourist Movement and Traffic in Split-Dalmatia County in Croatia is carried out as a part of the "IPA Adriatic CBC//N.0086/INTERMODAL" project. This paper briefly explains the big data used in the study and the results of the study. Furthermore, this paper investigates the main considerations when using telecom customer big data: data privacy and data quality. The paper concludes with GIS visualisation and proposes the further use of big data used in the study. © Authors 2017. CC BY 4.0 License.

关键词： big data

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international Workshops on database Systems for Advanced Applications, DASFAA 2017, 4th international Workshop on big data Management and Service, BDMS 2017, 2nd Workshop on big data Quality Management, BDQM 2017, 4th international Workshop on Semantic Computing and Personalization, SeCoP 2017, 1st international Workshop on data Management and Mining on MOOCs, DMMOOC 2017

International Workshops on Database Systems for Advanced App...

引用

international Workshops on database Systems for Advanced Applications, DASFAA 2017, 4th international Workshop on big data Management and Service, BDMS 2017, 2nd Workshop on big data Quality Management, BDQM 2017, 4th international Workshop on Semantic Computing and Personalization, SeCoP 2017, 1st international Workshop on data Management and Mining on MOOCs, DMMOOC 2017

ISBN: (纸本)9783319557045

The proceedings contain 37 papers. The special focus in this conference is on database Systems for Advanced Applications, big data Quality Management, big data Management and Service. The topics include: Automatically classify Chinese judgment documents utilizing machine learning algorithms;a partitioning scheme for big dynamic trees;optimization factor analysis of large-scale join queries on different platforms;an online prediction framework for dynamic service-generated QOS big data;discovering interesting co-location patterns interactively using ontologies;online formation of large tree-structured team;cell-based DBSCAN algorithm using minimum bounding rectangle criteria;time-aware and topic-based reviewer assignment;adaptive Bayesian network structure learning from big datasets;a novel approach for author name disambiguation using ranking confidence;capture missing values with inference on knowledge base;weakly-supervised named entity extraction using word representations;RDF data assessment based on metrics and improved pagerank algorithm;efficient web-based data imputation with graph model;a new schema design method for multi-tenant database;accelerating convolutional neural networks using fine-tuned backpropagation progress;a personalized learning strategy recommendation approach for programming learning;Wikipedia based short text classification method;an efficient Boolean expression index by compression and task assignment of peer grading in MOOCS.

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ACM international conference Proceeding Series

ACM International Conference Proceeding Series

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2nd international conference on big data Cloud and Applications, BDCA 2017

ISBN: (纸本)9781450348522

The proceedings contain 113 papers. The topics discussed include: big data analytics techniques in virtual screening for drug discovery;design a secure framework for cloud-based medical image storage;security in cloud-based medical image processing: requirements and approaches;towards an automatic generator of mathematical exercises based on semantic;build a morphosyntaxically annotated Amazigh corpus;neural network approach for fault detection in substations;data security and risks for IoT in intercommunicating objects;fully homomorphic encryption: searching over encrypted cloud data;revisiting BFR clustering algorithm for large scale gene regulatory network reconstruction using MapReduce;impact of selecting virtual machine with least load on tasks scheduling algorithms in cloud computing;cloud computing performance evaluation under dynamic resource utilization and traffic control;a hybrid approach for optimized composition of cloud services;data collect requirements model;a new cloud computing approach based SVM for relevant data extraction;survey of plagiarism detection approaches and big data techniques related to plagiarism candidate retrieval;towards clustering validation in big data Context;developing and performance evaluation of a new Arabic heavy/light stemmer;and revisiting BFR clustering algorithm for large scale gene regulatory network reconstruction using MapReduce.

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R²CEDM: A Rete-Based RFID Complex Event Detection Method 2nd

R<SUP>2</SUP>CEDM: A Rete-Based RFID Complex Event Detection...

引用

2nd international conference on data Mining and big data (DMBD)

作者： Peng, Xiaoli Zheng, Linjiang Liao, Ting Sichuan Univ Arts & Sci Sch Intelligent Mfg Dazhou 635000 Sichuan Peoples R China Chongqing Univ Coll Comp Sci Chongqing 400030 Peoples R China Inst Dazhou Intelligent Mfg Technol Dazhou 635000 Sichuan Peoples R China

ISBN: (纸本)9783319618456;9783319618449

In various RFID application scenarios, RFID generates real-time and inherent unreliable raw data continually, which contain valuable enterprises business event. How to detect valuable event from RFID raw data has becoming a key issue. A Rete-based RFID complex event detection method called (RCEDM)-C-2 is proposed. Firstly, alpha_detecting net is established to detect all attribute of RFID primitive events in (RCEDM)-C-2. Then beta_detecting net is used to assemble RFID events into RFID complex events with the business rules, and concerned RFID complex events is obtained. The comparative experiments show the proposed (RCEDM)-C-2 can effectively improve the processing efficiency.

关键词： Complex event detection RFID Rete Rule match

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IOP conference Series: Materials Science and Engineering

IOP Conference Series: Materials Science and Engineering

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2017 2nd international Seminar on Advances in Materials Science and Engineering, ISAMSE 2017

The proceedings contain 190 papers. The topics discussed include: A preconditioner for symmetric saddle point matrices;Security warning method and system for worker safety during live-line working;Research on electric field distribution of UHVDC transmission lines and body surface during live working;Comment on id-based remote data integrity checking with data privacy preserving;Metering error quantification under voltage and current waveform distortion;A simplified parsimonious higher order multivariate Markov chain model with new convergence condition;Image retrieval method based on metric learning for convolutional neural network;Bipolar-value fuzzy soft lie subalgebras;A simplified parsimonious higher order multivariate Markov chain model;A study on facial expressions recognition;Research on architecture of intelligent design platform for artificial neural network expert system;A tridiagonal parsimonious higher order multivariate Markov chain model;Evaluation research of small and medium-sized enterprise informatization on big data;A review of feature detection and match algorithms for localization and mapping;The study on the identity of property under operation on binary relation;Study of test script design methods for Web Service performance testing;The review and results of different methods for facial recognition;and Constraint genetic algorithm and its application in sintering proportioning.

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Machine Learning Software in Practice: Quo Vadis? 17

Machine Learning Software in Practice: Quo Vadis?

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23rd ACM SIGKDD international conference on Knowledge Discovery and data Mining (KDD)

作者： Pafka, Szilard Epoch 2644 30th St2nd Fl Santa Monica CA 90401 USA

ISBN: (纸本)9781450348874

Due to the hype in our industry in the last couple of years, there is a growing mismatch between software tools machine learning practitioners wish for, what they would truly need for their work, what's available (either commercially or open source) and what tool developers and researchers focus on. In this talk we will give a couple of examples of this mismatch. Several surveys and anecdotal evidence show that most practitioners work most of the time (at least in the modeling phase) with datasets that t in the RAM of a single server, therefore distributed computing tools are very of- ten overkill. Our benchmarks (available on github [1]) of the most widely used open source tools for binary classification (various implementations of algorithms such as linear methods, random forests, gradient boosted trees and neural networks) on such data show over 10x speed and over 10x RAM usage difference between various tools, with "big data" tools being the most inefficient. Significant performance gains have been obtained by those tools that incorporate various low-level (close to CPU and memory architecture) optimizations. Nevertheless, we will show that even the best tools show degrading performance on the multi-socket servers featuring a high number of cores, systems that have become widely accessible more recently. Finally, while most of this talk is about performance, we will also argue that machine learning tools that feature high-level easy-to-use APIs provide increasing productivity for practitioners and therefore are preferable.

关键词： binary classification software implementations training speed memory footprint accuracy

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