检索结果-内蒙古大学图书馆

A Fast Quartet tree heuristic for hierarchical clustering

PATTERN RECOGNITION 2011年第3期44卷 662-677页

作者： Cilibrasi, Rudi L. Vitanyi, Paul M. B. CWI Natl Res Inst Math & Comp Sci CWI NL-1098 XG Amsterdam Netherlands Univ Amsterdam Amsterdam Netherlands

The Minimum Quartet Tree Cost problem is to construct an optimal weight tree from the 3((n)(4)) weighted quartet topologies on n objects, where optimality means that the summed weight of the embedded quartet topologies is optimal (so it can be the case that the optimal tree embeds all quartets as nonoptimal topologies). We present a Monte Carlo heuristic, based on randomized hill-climbing, for approximating the optimal weight tree, given the quartet topology weights. The method repeatedly transforms a dendrogram, with all objects involved as leaves, achieving a monotonic approximation to the exact single globally optimal tree. The problem and the solution heuristic has been extensively used for general hierarchical clustering of nontree-like (non-phylogeny) data in various domains and across domains with heterogeneous data. We also present a greatly improved heuristic, reducing the running time by a factor of order a thousand to ten thousand. All this is implemented and available, as part of the CompLearn package. We compare performance and running time of the original and improved versions with those of UPGMA. BioNJ, and NJ, as implemented in the SplitsTree package on genomic data for which the latter are optimized. (C) 2010 Elsevier Ltd. All rights reserved.

关键词： data and knowledge visualization Pattern matching-Clustering-Algorithms/Similarity measures Pattern matching-Applications Hierarchical clustering Global optimization Monte Carlo method Quartet tree Randomized hill-climbing

来源：评论

学校读者我要写书评

暂无评论

A Learning Approach to SQL Query Results Ranking Using Skyline and Users' Current Navigational Behavior

引用

IEEE TRANSACTIONS ON knowledge AND data ENGINEERING 2013年第12期25卷 2683-2693页

作者： Chen, Zhiyuan Li, Tao Sun, Yanan Univ Maryland Baltimore Cty Dept Informat Syst Baltimore MD 21250 USA Florida Int Univ Sch Comp Sci Miami FL 33199 USA

Users often find that their queries against a database return too many answers, many of them irrelevant. A common solution is to rank the query results. The effectiveness of a ranking function depends on how well it captures users' preferences. However, database systems often do not have the complete information about users' preferences and users' preferences are often heterogeneous (i.e., some preferences are static and common to all users while some are dynamic and diverse). Existing solutions do not address these two issues. In this paper, we propose a novel approach to address these shortcomings: 1) it addresses the heterogeneous issue by using skyline to capture users' static and common preferences and using users' current navigational behavior to capture users' dynamic and diverse preferences;2) it addresses the incompleteness issue by using a machine learning technique to learn a ranking function based on training examples constructed from the above two types of information. Experimental results demonstrate the benefits of our approach.

关键词： data and knowledge visualization interactive data exploration and discovery

来源：评论

学校读者我要写书评

暂无评论

Visual Integration of Quantitative Proteomic data, Pathways, and Protein Interactions

引用

IEEE TRANSACTIONS ON visualization AND COMPUTER GRAPHICS 2010年第4期16卷 609-620页

作者： Jianu, Radu Yu, Kebing Cao, Lulu Nguyen, Vinh Salomon, Arthur R. Laidlaw, David H. Brown Univ Dept Comp Sci Providence RI 02912 USA Brown Univ Dept Chem Providence RI 02912 USA Brown Univ Ctr Genom & Prote Providence RI 02912 USA Brown Univ Dept Mol Biol Cell Biol & Biochem Providence RI 02912 USA

We introduce several novel visualization and interaction paradigms for visual analysis of published protein-protein interaction networks, canonical signaling pathway models, and quantitative proteomic data. We evaluate them anecdotally with domain scientists to demonstrate their ability to accelerate the proteomic analysis process. Our results suggest that structuring protein interaction networks around canonical signaling pathway models, exploring pathways globally and locally at the same time, and driving the analysis primarily by the experimental data, all accelerate the understanding of protein pathways. Concrete proteomic discoveries within T-cells, mast cells, and the insulin signaling pathway validate the findings. The aim of the paper is to introduce novel protein network visualization paradigms and anecdotally assess the opportunity of incorporating them into established proteomic applications. We also make available a prototype implementation of our methods, to be used and evaluated by the proteomic community.

关键词： Biological (genome or protein) databases data and knowledge visualization graphs and networks interactive data exploration and discovery visualization techniques and methodologies

来源：评论

学校读者我要写书评

暂无评论

visualization of Dynamic Network Evolution With Quantification of Node Attributes

引用

IEEE TRANSACTIONS ON NETWORK SCIENCE AND ENGINEERING 2021年第3期8卷 2316-2325页

作者： Kim, Minseo Korea Univ Sejong Campus Cultural Heritage & Smart Technol Convergence Edu Sejong South Korea

The effective visual exploration of dynamic networks has been one of the toughest challenges and an unsolved problem;however, it is very important to understand network evolution. Although many developments have been achieved in modeling evolutionary networks, the closely related task of visualizing continues to remain a major concern. Therefore, in this study, quantitative analysis is used to assign node attributes in the network topology, and then, the evolutionary process of networks is analyzed. By fixing the position of nodes, the possibility of a stationary shape of the network is suggested, and a more intuitive and comprehensive explanation of the enumeration of the types for the evolutionary process is provided. Further, a large amount of information is presented in this study in an extremely economical and accessible way by incorporating a circular layout and evolution laws, which offers a new approach for the estimation and evaluation of network evolution. Finally, this three-pronged approach-network analysis, quantitative method, and topological modeling-is expected to provide a revelatory insight into the principle of network evolution.

关键词： data visualization data models Computational modeling visualization Network topology Analytical models Painting Art Communication Networking and Information Technology data and knowledge visualization Evolution Image Processing and Computer Vision Simulation Modeling and visualization

来源：评论

学校读者我要写书评

暂无评论

Semi-Supervised Topological Analysis for Elucidating Hidden Structures in High-Dimensional Transcriptome datasets

引用

IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS 2021年第4期18卷 1620-1631页

作者： Feng, Tianshu Davila, Jaime, I Liu, Yuanhang Lin, Sangdi Huang, Shuai Wang, Chen Mayo Clin Dept Hlth Sci Res Rochester MN 55901 USA Univ Washington Dept Ind & Syst Engn Seattle WA 98195 USA Zillow Grp Seattle WA 98101 USA

Topological data analysis (TDA) is a powerful method for reducing data dimensionality, mining underlying data relationships, and intuitively representing the data structure. The Mapper algorithm is one such tool that projects high-dimensional data to 1-dimensional space by using a filter function that is subsequently used to reconstruct the data topology relationships. However, domain context information and prior knowledge have not been considered in current TDA modeling frameworks. Here, we report the development and evaluation of a semi-supervised topological analysis (STA) framework that incorporates discrete or continuously labeled data points and selects the most relevant filter functions accordingly. We validate the proposed STA framework with simulation data and then apply it to samples from Genotype-Tissue Expression data and ovarian cancer transcriptome datasets. The graphs generated by STA for these 2 datasets, based on gene expression profiles, are consistent with prior knowledge, thereby supporting the effectiveness of the proposed framework.

关键词： data models Bioinformatics data analysis Genomics Manganese data mining data structures data and knowledge visualization data mining bioinformatics (genome or protein) databases

来源：评论

学校读者我要写书评

暂无评论

StreamStory: Exploring Multivariate Time Series on Multiple Scales

引用

IEEE TRANSACTIONS ON visualization AND COMPUTER GRAPHICS 2019年第4期25卷 1788-1802页

作者： Stopar, Luka Skraba, Primoz Grobelnik, Marko Mladenic, Dunja Jozef Stefan Inst Jozef Stefan Int Postgrad Sch Ljubljana 1000 Slovenia Jozef Stefan Inst Ljubljana 1000 Slovenia

This paper presents an approach for the interactive visualization, exploration and interpretation of large multivariate time series. Interesting patterns in such datasets usually appear as periodic or recurrent behavior often caused by the interaction between variables. To identify such patterns, we summarize the data as conceptual states, modeling temporal dynamics as transitions between the states. This representation can visualize large datasets with potentially billions of examples. We extend the representation to multiple spatial granularities allowing the user to find patterns on multiple scales. The result is an interactive web-based tool called StreamStory. StreamStory couples the abstraction with several tools that map the abstractions back to domain-specific concepts using techniques from statistics and machine learning. It is aimed at users who are not experts in data analytics, minimizing the number of parameters to configure out-of-the-box. We use three real-world datasets to demonstrate how StreamStory can be used to perform three main visual analytics tasks: identify the main states of a complex system and map them back to data-specific concepts, find high-level and long-term periodic behavior and traverse the scales to identify which scales exhibit interesting phenomena. We find and interpret several known, as well as previously unknown patterns in these datasets.

关键词： Time series analysis visualization systems and software data and knowledge visualization markov processes multivariate visualization data mining

来源：评论

学校读者我要写书评

暂无评论

Microbloggers as Sensors for Public Transport Breakdowns

引用

IEEE INTERNET COMPUTING 2015年第6期19卷 18-25页

作者： Congosto, Mariluz Fuentes-Lorenzo, Damaris Sanchez, Luis Univ Carlos III Madrid Dept Telemat Engn E-28903 Getafe Spain

Microblogging has spread to fields where real-time awareness is crucial, such as predicting natural disasters or health outbreaks. Here, the authors harness observations and complaints from human sensors, collected through Twitter, to demonstrate how social sensing has the ability to detect breakdowns in a public transport network in real time, beyond official surveillance information. The system collects, filters, and processes the large datasets obtained to detect the daily problems in a public transport railway network of a major city and disseminate the results for user consumption through graphical rendering.

关键词： Twitter data Mining Real Time Systems Internet Monitoring Context Modeling Web And Internet Services visualization Collaborative Computing Internet Web Technologies data and knowledge visualization data Mining Web Based Services Computer Supported Collaborative Work

来源：评论

学校读者我要写书评

暂无评论

Ontology-based search for interactive digital maps

引用

IEEE INTELLIGENT SYSTEMS 2004年第3期19卷 80-86页

作者： Hübner, S Spittel, R Visser, U Vögele, TJ Univ Bremen Ctr Comp Technol TZI D-28359 Bremen Germany Niedersachs Umweltminist Koordinierungsstelle UDK GEIN D-30169 Hannover Germany

Our main objective is to develop user-centric services to support better governance, democratic processes, and a sustainable and balanced development of rural and urban areas around the North Sea. A bike trip example offers a detailed look at the GeoShare Network"s technologies, including ontologies for describing vocabularies and catalogs. We also discuss about the spatial data infrastructure consisting of a spatial reasoner, a Web catalog service, distributed Web map services, and a generic Web map client and about the ontology-based search for interactive digital maps.

关键词： Intelligent Web Services Semantic Web Internet Reasoning Services data and knowledge visualization

来源：评论

学校读者我要写书评

暂无评论

Graph signatures for visual analytics

引用

IEEE TRANSACTIONS ON visualization AND COMPUTER GRAPHICS 2006年第6期12卷 1399-1413页

作者： Wong, Pak Chung Foote, Harlan Chin, George, Jr. Mackey, Patrick Perrine, Ken Pacific NW Natl Lab Richland WA 99352 USA

We present a visual analytics technique to explore graphs using the concept of a data signature. A data signature, in our context, is a multidimensional vector that captures the local topology information surrounding each graph node. Signature vectors extracted from a graph are projected onto a low-dimensional scatterplot through the use of scaling. The resultant scatterplot, which reflects the similarities of the vectors, allows analysts to examine the graph structures and their corresponding real-life interpretations through repeated use of brushing and linking between the two visualizations. The interpretation of the graph structures is based on the outcomes of multiple participatory analysis sessions with intelligence analysts conducted by the authors at the Pacific Northwest National Laboratory. The paper first uses three public domain data sets with either well-known or obvious features to explain the rationale of our design and illustrate its results. More advanced examples are then used in a customized usability study to evaluate the effectiveness and efficiency of our approach. The study results reveal not only the limitations and weaknesses of the traditional approach based solely on graph visualization, but also the advantages and strengths of our signature-guided approach presented in the paper.

关键词： data and knowledge visualization information visualization visualization techniques and methodologies graphs and networks

来源：评论

学校读者我要写书评

暂无评论

D-Map: Random Walking on Gene Network Inference Maps Towards differential Avenue Discovery

引用

IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS 2017年第2期14卷 484-490页

作者： Athanasiadis, Emmanouil Bourdakou, Marilena Spyrou, George Acad Athens Syst Biol Ctr Biomed Res Fdn 4 Soranou Ephessiou Athens 11527 Greece Univ Athens Dept Informat & Telecommun Ilissia 15784 Greece

Differential rewiring of cellular interaction networks between disease and healthy state is of great importance. Through a systems level approach, malfunctioned mechanisms that are absent in the normal cases, may enlighten the key-players in terms of genes and their interaction chains related to disease. We have developed D-Map, a publicly available user-friendly web application, capable of generating and manipulating advanced differential networks by combining state-of-the-art inference reconstruction methods with random walk simulations. The inputs are expression profiles obtained from the Gene Expression Omnibus and a gene list under investigation. Differential networks may be visualized and interpreted through the use of D-Map interface, where display of the disease, the normal and the common state can be performed, interactively. A case study scenario concerning Alzheimer's disease, as well as breast, lung, and bladder cancer was conducted in order to demonstrate the usefulness of the proposed methodology to different disease types. Findings were consistent with the current bibliography, and the provided interaction lists may be further explored towards novel biological insights of the investigated diseases.

关键词： data and knowledge visualization graphs and networks inference networks random walks

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：