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Graph Analysis And Visualization

Author: Richard Brath
Publisher: John Wiley & Sons
ISBN: 1118845870
Size: 66.39 MB
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Wring more out of the data with a scientific approach toanalysis Graph Analysis and Visualization brings graph theory outof the lab and into the real world. Using sophisticated methods andtools that span analysis functions, this guide shows you how toexploit graph and network analytic techniques to enable thediscovery of new business insights and opportunities. Published infull color, the book describes the process of creating powerfulvisualizations using a rich and engaging set of examples fromsports, finance, marketing, security, social media, and more. Youwill find practical guidance toward pattern identification andusing various data sources, including Big Data, plus clearinstruction on the use of software and programming. The companionwebsite offers data sets, full code examples in Python, and linksto all the tools covered in the book. Science has already reaped the benefit of network and graphtheory, which has powered breakthroughs in physics, economics,genetics, and more. This book brings those proven techniques intothe world of business, finance, strategy, and design, helpingextract more information from data and better communicate theresults to decision-makers. Study graphical examples of networks using clear and insightfulvisualizations Analyze specifically-curated, easy-to-use data sets fromvarious industries Learn the software tools and programming languages that extractinsights from data Code examples using the popular Python programminglanguage There is a tremendous body of scientific work on network andgraph theory, but very little of it directly applies to analystfunctions outside of the core sciences – until now. Writtenfor those seeking empirically based, systematic analysis methodsand powerful tools that apply outside the lab, Graph Analysisand Visualization is a thorough, authoritative resource.

Social Network Forensics Cyber Security And Machine Learning

Author: P. Venkata Krishna
Publisher: Springer
ISBN: 981131456X
Size: 71.35 MB
Format: PDF, Kindle
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This book discusses the issues and challenges in Online Social Networks (OSNs). It highlights various aspects of OSNs consisting of novel social network strategies and the development of services using different computing models. Moreover, the book investigates how OSNs are impacted by cutting-edge innovations.

Technology And Applications Of Polymers Derived From Biomass

Author: Syed Ali Ashter
Publisher: William Andrew
ISBN: 0323511163
Size: 56.85 MB
Format: PDF, Mobi
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Technology and Applications of Polymers Derived from Biomass explores the range of different possible routes from biomass to polymeric materials, including the value and limitations of using biomass in material applications and a comparison of petrochemical-derived polymers and bio-based polymers. The book discusses biomass sources, types, chemistry and handling concerns. It covers the manufacture of industrial chemicals from biomass and the derivation of monomers and polymers from biomass. It also details the processing and applications of biomass-derived polymers to enable materials scientists and engineers realize the potential of biomass as a sustainable source of polymers, including plastics and elastomers. The book is a one-stop-shop reference—giving students a basic understanding of the technology and how the material can be applied to industrial processes they will face in the workforce, and giving materials engineers and product designers the information they need to make more informed material selection decisions. Provides fundamental understanding of an increasingly important approach to sourcing polymeric materials Includes actionable, relevant information to enable materials engineers and product designers consider biomass-derived polymers in the products they are developing Discusses the environmental impact of biomass conversion to help readers improve the sustainability of their operations Compares petrochemical-derived polymers with bio-based polymers

Graph Databases

Author: Ian Robinson
Publisher: "O'Reilly Media, Inc."
ISBN: 1491930861
Size: 58.79 MB
Format: PDF, Docs
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Discover how graph databases can help you manage and query highly connected data. With this practical book, you’ll learn how to design and implement a graph database that brings the power of graphs to bear on a broad range of problem domains. Whether you want to speed up your response to user queries or build a database that can adapt as your business evolves, this book shows you how to apply the schema-free graph model to real-world problems. This second edition includes new code samples and diagrams, using the latest Neo4j syntax, as well as information on new functionality. Learn how different organizations are using graph databases to outperform their competitors. With this book’s data modeling, query, and code examples, you’ll quickly be able to implement your own solution. Model data with the Cypher query language and property graph model Learn best practices and common pitfalls when modeling with graphs Plan and implement a graph database solution in test-driven fashion Explore real-world examples to learn how and why organizations use a graph database Understand common patterns and components of graph database architecture Use analytical techniques and algorithms to mine graph database information

Discovery Science

Author: Jean-Francois Boulicaut
Publisher: Springer Science & Business Media
ISBN: 3540884106
Size: 59.46 MB
Format: PDF, ePub, Docs
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This book constitutes the refereed proceedings of the 11th International Conference on Discovery Science, DS 2008, held in Budapest, Hungary, in October 2008, co-located with the 19th International Conference on Algorithmic Learning Theory, ALT 2008. The 26 revised long papers presented together with 5 invited papers were carefully reviewed and selected from 58 submissions. The papers address all current issues in the area of development and analysis of methods for intelligent data analysis, knowledge discovery and machine learning, as well as their application to scientific knowledge discovery. The papers are organized in topical sections on learning, feature selection, associations, discovery processes, learning and chemistry, clustering, structured data, and text analysis.

Knowledge Discovery From Sensor Data

Author: Mohamed Medhat Gaber
Publisher: Springer Science & Business Media
ISBN: 3642125182
Size: 63.42 MB
Format: PDF, ePub, Mobi
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This book contains thoroughly refereed extended papers from the Second International Workshop on Knowledge Discovery from Sensor Data, Sensor-KDD 2008, held in Las Vegas, NV, USA, in August 2008. The 12 revised papers presented together with an invited paper were carefully reviewed and selected from numerous submissions. The papers feature important aspects of knowledge discovery from sensor data, e.g., data mining for diagnostic debugging; incremental histogram distribution for change detection; situation-aware adaptive visualization; WiFi mining; mobile sensor data mining; incremental anomaly detection; and spatiotemporal neighborhood discovery for sensor data.

Advances In Knowledge Discovery And Data Mining

Author: Ming-Syan Cheng
Publisher: Springer Science & Business Media
ISBN: 3540437045
Size: 18.40 MB
Format: PDF, Mobi
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This book constitutes the refereed proceedings of the 6th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2002, held in Taipei, Taiwan, in May 2002. The 32 revised full papers and 20 short papers presented together with 4 invited contributions were carefully reviewed and selected from a total of 128 submissions. The papers are organized in topical sections on association rules; classification; interestingness; sequence mining; clustering; Web mining; semi-structure and concept mining; data warehouse and data cube; bio-data mining; temporal mining; and outliers, missing data, and causation.

Business Process Management Workshops

Author: Ernest Teniente
Publisher: Springer
ISBN: 331974030X
Size: 19.48 MB
Format: PDF, ePub, Docs
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This book constitutes revised papers from the eleven International Workshops held at the 15th International Conference on Business Process Management, BPM 2017, in Barcelona, Spain, in September 2017: BPAI 2017 – 1st International Workshop on Business Process Innovation with Artificial Intelligence; BPI 2017 – 13th International Workshop on Business Process Intelligence; BP-Meet-IoT 2017 – 1st International Workshop on Ubiquitous Business Processes Meeting Internet-of-Things; BPMS2 2017 – 10th Workshop on Social and Human Aspects of Business Process Management; ‐ CBPM 2017 – 1st International Workshop on Cognitive Business Process Management; CCABPM 2017 – 1st International Workshop on Cross-cutting Aspects of Business Process Modeling; DeHMiMoP 2017 – 5th International Workshop on Declarative/Decision/Hybrid Mining & Modeling for Business Processes; QD-PA 2017 – 1st International Workshop on Quality Data for Process Analytics; REBPM 2017 – 3rd International Workshop on Interrelations between Requirements Engineering and Business Process Management; SPBP 2017 – 1st Workshop on Security and Privacy-enhanced Business Process Management; TAProViz-PQ-IWPE 2017 –Joint International BPM 2017 Workshops on Theory and Application of Visualizations and Human-centric Aspects in Processes (TAProViz'17), Process Querying (PQ'17) and Process Engineering (IWPE17). The 44 full and 11 short papers presented in this volume were carefully reviewed and selected from 99 submissions.

Clojure For Data Science

Author: Henry Garner
Publisher: Packt Publishing Ltd
ISBN: 1784397504
Size: 16.88 MB
Format: PDF, ePub
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Statistics, big data, and machine learning for Clojure programmers About This Book Write code using Clojure to harness the power of your data Discover the libraries and frameworks that will help you succeed A practical guide to understanding how the Clojure programming language can be used to derive insights from data Who This Book Is For This book is aimed at developers who are already productive in Clojure but who are overwhelmed by the breadth and depth of understanding required to be effective in the field of data science. Whether you're tasked with delivering a specific analytics project or simply suspect that you could be deriving more value from your data, this book will inspire you with the opportunities–and inform you of the risks–that exist in data of all shapes and sizes. What You Will Learn Perform hypothesis testing and understand feature selection and statistical significance to interpret your results with confidence Implement the core machine learning techniques of regression, classification, clustering and recommendation Understand the importance of the value of simple statistics and distributions in exploratory data analysis Scale algorithms to web-sized datasets efficiently using distributed programming models on Hadoop and Spark Apply suitable analytic approaches for text, graph, and time series data Interpret the terminology that you will encounter in technical papers Import libraries from other JVM languages such as Java and Scala Communicate your findings clearly and convincingly to nontechnical colleagues In Detail The term “data science” has been widely used to define this new profession that is expected to interpret vast datasets and translate them to improved decision-making and performance. Clojure is a powerful language that combines the interactivity of a scripting language with the speed of a compiled language. Together with its rich ecosystem of native libraries and an extremely simple and consistent functional approach to data manipulation, which maps closely to mathematical formula, it is an ideal, practical, and flexible language to meet a data scientist's diverse needs. Taking you on a journey from simple summary statistics to sophisticated machine learning algorithms, this book shows how the Clojure programming language can be used to derive insights from data. Data scientists often forge a novel path, and you'll see how to make use of Clojure's Java interoperability capabilities to access libraries such as Mahout and Mllib for which Clojure wrappers don't yet exist. Even seasoned Clojure developers will develop a deeper appreciation for their language's flexibility! You'll learn how to apply statistical thinking to your own data and use Clojure to explore, analyze, and visualize it in a technically and statistically robust way. You can also use Incanter for local data processing and ClojureScript to present interactive visualisations and understand how distributed platforms such as Hadoop sand Spark's MapReduce and GraphX's BSP solve the challenges of data analysis at scale, and how to explain algorithms using those programming models. Above all, by following the explanations in this book, you'll learn not just how to be effective using the current state-of-the-art methods in data science, but why such methods work so that you can continue to be productive as the field evolves into the future. Style and approach This is a practical guide to data science that teaches theory by example through the libraries and frameworks accessible from the Clojure programming language.