Social Network Analysis

Praise for the Third Edition: "This is one of the best books available. Its excellent organizational structure allows quick reference to specific models and its clear presentation . . . solidifies the understanding of the concepts being presented."IIE Transactions on Operations EngineeringThoroughly revised and expanded to reflect the latest developments in the field, Fundamentals of Queueing Theory, Fourth Edition continues to present the basic statistical principles that are necessary to analyze the probabilistic nature of queues. Rather than presenting a narrow focus on the subject, this update illustrates the wide-reaching, fundamental concepts in queueing theory and its applications to diverse areas such as computer science, engineering, business, and operations research.This update takes a numerical approach to understanding and making probable estimations relating to queues, with a comprehensive outline of simple and more advanced queueing models. Newly featured topics of the Fourth Edition include:Retrial queuesApproximations for queueing networksNumerical inversion of transformsDetermining the appropriate number of servers to balance quality and cost of serviceEach chapter provides a self-contained presentation of key concepts and formulae, allowing readers to work with each section independently, while a summary table at the end of the book outlines the types of queues that have been discussed and their results. In addition, two new appendices have been added, discussing transforms and generating functions as well as the fundamentals of differential and difference equations. New examples are now included along with problems that incorporate QtsPlus software, which is freely available via the book's related Web site.With its accessible style and wealth of real-world examples, Fundamentals of Queueing Theory, Fourth Edition is an ideal book for courses on queueing theory at the upper-undergraduate and graduate levels. It is also a valuable resource for researchers and practitioners who analyze congestion in the fields of telecommunications, transportation, aviation, and management science.

Fundamentals of Queueing Theory

The Visual Display of Quantitative Information

This is a survey on graph visualization and navigation techniques, as used in information visualization. Graphs appear in numerous applications such as Web browsing, state-transition diagrams, and data structures. The ability to visualize and to navigate in these potentially large, abstract graphs is often a crucial part of an application. Information visualization has specific requirements, which means that this survey approaches the results of traditional graph drawing from a different perspective.

/pdf/graph-visualization-and-navigation-in-information-24tisrjfna.pdf

Graph visualization and navigation in information visualization: A survey

1. Introduction to text mining 2. Core text mining operations 3. Text mining preprocessing techniques 4. Categorization 5. Clustering 6. Information extraction 7. Probabilistic models for Information extraction 8. Preprocessing applications using probabilistic and hybrid approaches 9. Presentation-layer considerations for browsing and query refinement 10. Visualization approaches 11. Link analysis 12. Text mining applications Appendix Bibliography.

/pdf/the-text-mining-handbook-advanced-approaches-in-analyzing-ge55wa29fm.pdf

The Text Mining Handbook: Advanced Approaches in Analyzing Unstructured Data

The rapid growth of data in large databases, such as text databases and scientific databases, requires efficient computer methods for automating analyses of the data with the goal of acquiring knowledges or making discoveries. Because the analyses of data are generally so expensive, most parts in databases remains as raw, unanalyzed primary data. Technology from machine learning (ML) will offer efficient tools for the intelligent analyses of the data using generalization ability. Generalization is an important ability specific to inductive learning that will predict unseen data with high accuracy based on learned concepts from training examples. In this article, we apply ML to text‐database analyses and knowledge acquisitions from text databases. We propose a completely new approach to the problem of text classification and extracting keywords by using ML techniques. We introduce a class of representations for classifying text data based on decision trees; (i.e., decision trees over attributes on strings)...

A machine learning approach to knowledge acquisitions from text databases

We propose a new method for representing tree structures with historical information. We call this method Ripple Presentation. Categories of nodes are represented by the angles of edges and elapsed time is represented by the length of the edges. In this way, the method can express both the time series and categories, which has been diffic lt to achieve with either tree structures or lists. As a result, users can nderstand the overall information from their viewpoint view and discover target information effectively. We applied the method to trackback links of Weblog articles and the latest articles of News sites using RSS on Web as a resource.

/pdf/ripple-presentation-for-tree-structures-with-historical-zfmw83kw48.pdf

Ripple presentation for tree structures with historical information

Treemap is a visualization method for hierarchical structures in which nodes are drawn as rectangles and arranged in a nested style. Several variations of Treemap have been developed to represent different types of data. In this paper, we propose an Edge Equalized Treemap, a representation that embeds visual data such as a bar chart in leaf rectangles. This representation is characterized by leaf rectangles of equal widths. Because their widths are equal, the scale intervals of charts in a leaf rectangle can be unified, meaning that we can compare charts simply by looking at them. We compare the Edge Equalized Treemap with existing layout methods, and demonstrate the usefulness of our approach.

/pdf/edge-equalized-treemaps-2kuji6afld.pdf

Edge Equalized Treemaps

Widespread use of GPS terminals has made it possible to collect geospatial movement data, and visualization is an effective method to understand such data. However, for large scale movement analysis, because the data set includes complex movements of individuals, it is difficult to understand using naive visualization methods. In order to solve this problem, we developed a visualization technique that can represent large scale movement data in an aggregate manner. This visualization technique has two representations: "amoeba representation" and "amoeba colony representation." Amoeba representation represents the distance moved from a point in any direction with map scale in a geographical space, and amoeba colony representation represents movements over a wide geographical space.

/pdf/directional-aggregate-visualization-of-large-scale-movement-m5gidlxh3l.pdf

Directional aggregate visualization of large scale movement data

Handwriting in computer environments satisfies many requirements that are necessary to support creative activities, as it is easy to use, natural, flexible, and informal. This article proposes a tool to support creative activities using handwriting. The tool has the following features: (1) It is targeted for use in processing diagrams with logical structures. (2) It provides a handwriting input interface. (3) It maintains the handwritten feel of diagrams. (4) It supports creative activities intellectually and actively. The architecture and the behavior of the tool are explained using some screen shots of a prototype.

Kazuo Misue

Papers

A machine learning approach to knowledge acquisitions from text databases

Ripple presentation for tree structures with historical information

Edge Equalized Treemaps

Directional aggregate visualization of large scale movement data

A handwriting tool to support creative activities