检索结果-内蒙古大学图书馆

44th ACM SIGMOD International conference on Management of data, SIGMOD 2018

ISBN: (纸本)9781450317436

The proceedings contain 159 papers. The topics discussed include: robust entity resolution using random graphs;deep learning for entity matching: a design space exploration;synthesizing type-detection logic for rich semantic data types using open-source code;data citation: giving credit where credit is due;EKTELO: a framework for defining differentially-private computations;computation reuse in analytics job service at Microsoft;P-Store: an elastic database system with predictive provisioning;Apache Calcite: a foundational framework for optimized query processing over heterogeneous data sources;catching numeric inconsistencies in graphs;TurboGraph++: a scalable and fast graph analytics system;building a Bw-Tree takes more than just buzz words;Dostoevsky: better space-time trade-offs for LSM-tree based key-value stores via adaptive removal of superfluous merging;efficient selection of geospatial data on maps for interactive and visualized exploration;robust, scalable, real-time event time series aggregation at Twitter;TcpRT: instrument and diagnostic analysis system for service quality of cloud databases at massive scale in real-time;machine learning for data management: problems and solutions;Amazon Aurora: on avoiding distributed consensus for I/Os, commits, and membership changes;Eon Mode: bringing the vertica columnar database to the cloud;randomized algorithms accelerated over CPU-GPU for ultra-high dimensional similarity search;BOOMER: blending visual formulation and processing of p-homomorphic queries on large networks;and navigating the data lake with datamaran: automatically extracting structure from log datasets.

关键词：

来源：评论

学校读者我要写书评

暂无评论

6th International conference on Mining Intelligence and Knowledge exploration, MIKE 2018

6th International Conference on Mining Intelligence and Know...

引用

6th International conference on Mining Intelligence and Knowledge exploration, MIKE 2018

ISBN: (纸本)9783030059170

The proceedings contain 33 papers. The special focus in this conference is on Mining Intelligence and Knowledge exploration. The topics include: Categorical modeling method of intelligent WorkFlow;classification of dengue serotypes using protein sequence based on rule extraction from neural network;orienting social event streams as data stories;software driven optimal design for maintenance man hour;modeling trajectory data as a directed graph;connected cars traffic flow balancing based on classification and calibration;identification and control of a car speed dynamics using artificial intelligence;industry 4.0, intelligent visual assisted picking approach;Detection and mapping of a toxic cloud using UAVs and emergent techniques;Meaningful clusterings of recurrent neural network activations for NLP;convolutional neural networks for multi-class intrusion detection system;wraudit: A tool to transparently monitor web resources’ integrity;using stigmergy to incorporate the time into artificial neural networks;modeling sustainability reporting with ternary attractor neural networks;analysing a periodical and multi-dimensional time series;stock price forecasting over adaptive timescale using supervised learning and receptive fields;Periodically diluted BEGNN model of corruption perception;neural machine translation with recurrent highway networks;a comparative study of methods used in the analysis and prediction of financial data;skin lesion images segmentation: A survey of the state-of-the-art;automatic extraction of structured information from drug descriptions;skin lesion segmentation using enhanced unified Markov random field;texture classification using deep convolutional neural network with ensemble learning;a novel decision tree approach for the handling of time series;reference metadata extraction from Korean research papers.

关键词：

来源：评论

学校读者我要写书评

暂无评论

22nd East-European conference on Advances in databases and Information Systems, ADBIS 2018

22nd East-European Conference on Advances in Databases and I...

引用

22nd East-European conference on Advances in databases and Information Systems, ADBIS 2018

ISBN: (纸本)9783319983974

The proceedings contain 19 papers. The special focus in this conference is on Advances in databases and Information Systems. The topics include: data Quality in a Big data Context;integrating Approximate String Matching with Phonetic String Similarity;cost-Based Sharing and Recycling ofÂ (Intermediate) Results in dataflow Programs;ATUN-HL: Auto Tuning of Hybrid Layouts Using Workload and data Characteristics;set Similarity Joins with Complex Expressions on Distributed Platforms;deterministic Model for Distributed Speculative Stream Processing;large-Scale Real-Time News Recommendation Based on Semantic data analysis and Users’ Implicit andÂ Explicit Behaviors;matBase Constraint Sets Coherence and Minimality Enforcement Algorithms;integration of Unsound data in P2P Systems;spatio-Temporal data Mining of Major European River and Mountain Names Reveals Their Near Eastern and African Origins;query Rewriting for Heterogeneous data Lakes;rawVis: visual exploration over Raw data;extended Margin and Soft Balanced Strategies in Active Learning;location-Awareness in Time Series Compression;Efficient SPARQL Evaluation on Stratified RDF data with Meta-data;SIMD Vectorized Hashing for Grouped Aggregation;selecting Sketches for Similarity Search.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Enhance SSHE safety, security, health and environment performance statistics dashboard application

Enhance SSHE safety, security, health and environment perfor...

引用

Offshore Technology conference Asia 2018, OTCA 2018

作者： Boonchaiyutasak, Jindarach Saengpoo, Atchara Klunngien, Chagun PTT Exploration and Production PLC United States

ISBN: (纸本)9781510862159

To enhance company's effectiveness in SSHE (Safety, Security, Health and Environment) management a high-level dashboard has been developed to provide performance monitoring using high visual-impact indicators. The Performance Statistics Dashboard (PSD) is designed to improve management communication of SSHE performance by providing wider use and increased flexibility of data integration with improved forecasting and reporting. The new features of the PSD include centralized data storage, monitoring and analysis enabling reporting on a compatible basis with stated global and sector SSHE information such as the International Association of Oil & Gas Producers (IOGP). The modularization of each component is used in supporting company, organization, assets and activities. The PSD application shows the status of performance statistics in real time through traffic lights and can generate statistics reports for graphical and data analysis at all levels. Moreover, the dashboard has a forecasting capability which can automatically generate and calculate predictive statistics based on historical data. PSD has been effectively implemented throughout PTTEP and all its Operating Asset. The system contributes to more effective decision making, and ensures SSHE data that is stored can be accessed and summarized through a single user interface to provide accurate and effective controlled real-time SSHE performance in all areas. Key benefits include: - Significantly reduced human errors in the calculation of SSHE statistics - Increased impact of SSHE performance communication - Increased precision and accuracy of data - Eliminated redundant reporting - Consistency across various sources - Intuitive data accessibility for user - Unlocked time zone operation. © 2018 Offshore Technology conference.

关键词： Decision making

来源：评论

学校读者我要写书评

暂无评论

Enabling data science for the majority 45th

Enabling data science for the majority

引用

45th International conference on Very Large data Bases, VLDB 2019

作者： Parameswaran, Aditya University of California Berkeley United States

Despite great strides in the generation, collection, and processing of data at scale, data science is still extremely inconvenient for the vast majority of the population. The driving goal of our research, over the past half decade, has been to make it easy for individuals and teams-regardless of programming or analysis expertise-manage, analyze, make sense of, and draw insights from large datasets. In this article, we reflect on a comprehensive suite of tools that we've been building to empower everyone to perform data science more efficiently and effortlessly, including dataSPREAD, a scalable spreadsheet tool that combines the benefits of spreadsheets and databases, and ZENVISAGE, a visual exploration tool that accelerates the discovery of trends or patterns. Our tools have been developed in collaboration with experts in various disciplines, including neuroscience, battery science, genomics, astrophysics, and ad analytics. We will discuss some of the key technical challenges underlying the development of these tools, and how we addressed them, drawing from ideas in multiple disciplines. In the process, we will outline a research agenda for tool development to empower everyone to tap into the hidden potential in their datasets at scale. © 2019 VLDB Endowment.

关键词： Large dataset

来源：评论

学校读者我要写书评

暂无评论

Supporting Exploratory Code Search with Differencing and visualization 25

Supporting Exploratory Code Search with Differencing and Vis...

引用

25th IEEE International conference on Software analysis, Evolution and Reengineering (SANER)

作者： Liu, Wenjian Peng, Xin Xing, Zhenchang Li, Junyi Xie, Bing Zhao, Wenyun Fudan Univ Sch Comp Sci Shanghai Peoples R China Fudan Univ Shanghai Key Lab Data Sci Shanghai Peoples R China Shanghai Inst Intelligent Elect & Syst Shanghai Peoples R China Australian Natl Univ Res Sch Comp Sci Canberra ACT Australia Peking Univ Sch Elect Engn & Comp Sci Beijing Peoples R China

ISBN: (纸本)9781538649695

Searching and reusing online code has become a common practice in software development. Two important characteristics of online code have not been carefully considered in current tool support. First, many pieces of online code are largely similar but subtly different. Second, several pieces of code may form complex relations through their differences. These two characteristics make it difficult to properly rank online code to a search query and reduce the efficiency of examining search results. In this paper, we present an exploratory online code search approach that explicitly takes into account the above two characteristics of online code. Given a list of methods returned for a search query, our approach uses clone detection and code differencing techniques to analyze both commonalities and differences among the methods in the search results. It then produces an exploration graph that visualizes the method differences and the relationships of methods through their differences. The exploration graph allows developers to explore search results in a structured view of different method groups present in the search results, and turns implicit code differences into visual cues to help developers navigate the search results. We implement our approach in a web-based tool called CodeNuance. We conduct experiments to evaluate the effectiveness of our CodeNuance tool for search results examination, compared with ranked-list and code-clustering based search results examination. We also compare the performance and user behavior differences in using our tool and other exploratory code search tools.

关键词： Tools Search engines Cloning Java Software Complexity theory Codes Search engines Complexity theory computer software Java Java programming language Searches Differentiation Cloning visualization

来源：评论

学校读者我要写书评

暂无评论

A Transfer Entropy Based visual Analytics System for Identifying Causality of Critical Hardware Failures Case Study: CPU Failures in the K Computer 18th

A Transfer Entropy Based Visual Analytics System for Identif...

引用

18th Annual Asia Simulation conference (AsiaSim)

作者： Koiso, Kazuki Sakamoto, Naohisa Nonaka, Jorji Shoji, Fumiyoshi Kobe Univ Grad Sch Syst Informat Kobe Hyogo Japan RIKEN Ctr Computat Sci Kobe Hyogo Japan

ISBN: (纸本)9789811328534;9789811328527

Large-scale scientific computing facilities usually operate expensive HPC (High Performance Computing) systems, which have their computational and storage resources shared with the authorized users. On such shared resource systems, a continuous and stable operation is fundamental for providing the necessary hardware resources for the different user needs, including large-scale numerical simulations, which are the main targets of such large-scale facilities. For instance, the K computer installed at the R-CCS (RIKEN Center for Computational Science), in Kobe, Japan, enables the users to continuously run large jobs with tens of thousands of nodes (a maximum of 36,864 computational nodes) for up to 24 h, and a huge job by using the entire K computer system (82,944 computational nodes) for up to 8 h. Critical hardware failures can directly impact the affected job, and may also indirectly impact the scheduled subsequent jobs. To monitor the health condition of the K computer and its supporting facility, a large number of sensors has been providing a vast amount of measured data. Since it is almost impossible to analyze the entire data in real-time, these information has been stored as log data files for post-hoc analysis. In this work, we propose a visual analytics system which uses these big log data files to identify the possible causes of the critical hardware failures. We focused on the transfer entropy technique for quantifying the "causality" between the possible cause and the critical hardware failure. As a case study, we focused on the critical CPU failures, which required subsequent substitution, and utilized the log files corresponding to the measured temperatures of the cooling system such as air and water. We evaluated the usability of our proposed system, by conducting practical evaluations via a group of experts who directly works on the K computer system operation. The positive and negative feedbacks obtained from this evaluation will be considered for the

关键词： data exploration Failure analysis High performance computing system Log data Causality Transfer entropy

来源：评论

学校读者我要写书评

暂无评论

Exploring the Role of Sound in Augmenting visualization to Enhance User Engagement 11

Exploring the Role of Sound in Augmenting Visualization to E...

引用

IEEE Pacific visualization Symposium (IEEE PacificVis)

作者： Du, Meng Chou, Jia-Kai Ma, Chen Chandrasegaran, Senthil Ma, Kwan-Liu Univ Calif Davis Davis CA 95616 USA

ISBN: (纸本)9781538614242

Studies on augmenting visualization with sound are typically based on the assumption that sound can be complementary and assist in data analysis tasks. While sound promotes a different sense of engagement than vision, we conjecture that by augmenting non-speech audio to a visualization can not only help enhance the users' perception of the data but also increase their engagement with the data exploration process. We have designed a preliminary user study to test users' performance and engagement while exploring in a data visualization system under two different settings: visual-only and audiovisual. For our study, we used basketball player movement data in a game and created an interactive visualization system with three linked views. We supplemented sound to the visualization to enhance the users' understanding of a team's offensive/defensive behavior. The results of our study suggest that we need to better understand the effect of sound choice and encoding before considering engagement. We also find that sound can be useful to draw novice users' attention to patterns or anomalies in the data. Finally, we propose follow-up studies with designs informed by the findings from this study.

关键词： sound-augmented visualization engagement

来源：评论

学校读者我要写书评

暂无评论

ImageX - Explore and Search Local/Private Images 24th

ImageX - Explore and Search Local/Private Images

引用

24th International conference on MultiMedia Modeling (MMM)

作者： Hezel, Nico Barthel, Kai Uwe Jung, Klaus HTW Berlin Univ Appl Sci Visual Comp Grp Wilhelminenhofstr 75a D-12459 Berlin Germany

ISBN: (纸本)9783319736006;9783319735993

In this paper we present a system to visually explore and search large sets of untagged images, running on common operating systems and consumer hardware. High quality image descriptors are computed using activations of a convolutional neural network. By applying normalization and a principal component analysis of the activations compact feature vectors of only 64 bytes are generated. The L1-distances for these feature vectors can be calculated very fast using a novel computation approach and allows search-by-example queries to be processed in fractions of a second. We further show how entire image collections can be transferred into hierarchical image graphs and describe a scheme to explore this complex data structure in an intuitive way. To enable keyword search for untagged images, reference features for common keywords are generated. These features are constructed by collecting and clustering examples images from the web.

关键词： Image exploration visualization CBIR Keyword search

来源：评论

学校读者我要写书评

暂无评论

Patterns and Sequences: Interactive exploration of Clickstreams to Understand Common Visitor Paths

引用

IEEE TRANSACTIONS ON visualIZATION AND COMPUTER GRAPHICS 2017年第1期23卷 321-330页

作者： Liu, Zhicheng Wang, Yang Dontcheva, Mira Hoffman, Matthew Walker, Seth Wilson, Alan Adobe Res San Jose CA USA Univ Calif Davis Davis CA USA Adobe Syst Inc San Jose CA USA

Modern web clickstream data consists of long, high-dimensional sequences of multivariate events, making it difficult to analyze. Following the overarching principle that the visual interface should provide information about the dataset at multiple levels of granularity and allow users to easily navigate across these levels, we identify four levels of granularity in clickstream analysis: patterns, segments, sequences and events. We present an analytic pipeline consisting of three stages: pattern mining, pattern pruning and coordinated exploration between patterns and sequences. Based on this approach, we discuss properties of maximal sequential patterns, propose methods to reduce the number of patterns and describe design considerations for visualizing the extracted sequential patterns and the corresponding raw sequences. We demonstrate the viability of our approach through an analysis scenario and discuss the strengths and limitations of the methods based on user feedback.

关键词： Clickstream data sequence mining visual analytics event sequences

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：