Download or read book Parameterized Algorithmics for Network Analysis Clustering Querying written by Christian Komusiewicz and published by Univerlagtuberlin. This book was released on 2011 with total page 181 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Parameterized Algorithmics for Network Analysis Clustering Querying written by Christian Komusiewicz and published by . This book was released on 2011 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Parameterized and Exact Computation written by Dimitrios M. Thilikos and published by Springer. This book was released on 2012-08-30 with total page 283 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 7th International Symposium on Parameterized and Exact Computation, IPEC 2012, in Ljubljana, Slovenia, in September 2012. The 21 revised full papers presented together with 2 keynote talks were carefully reviewed and selected from 37 submissions. The topics addressed cover research in all aspects of parameterized/exact algorithms and complexity including but are not limited to new techniques for the design and analysis of parameterized and exact algorithms; fixed-parameter tractability results; parameterized complexity theory; relationship between parameterized complexity and traditional complexity classifications; applications of parameterized and exact computation; and implementation issues of parameterized and exact algorithms.
Download or read book Mathematical Foundations of Computer Science 2013 written by Krishnendu Chatterjee and published by Springer. This book was released on 2013-08-16 with total page 869 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the thoroughly refereed conference proceedings of the 38th International Symposium on Mathematical Foundations of Computer Science, MFCS 2013, held in Klosterneuburg, Austria, in August 2013. The 67 revised full papers presented together with six invited talks were carefully selected from 191 submissions. Topics covered include algorithmic game theory, algorithmic learning theory, algorithms and data structures, automata, formal languages, bioinformatics, complexity, computational geometry, computer-assisted reasoning, concurrency theory, databases and knowledge-based systems, foundations of computing, logic in computer science, models of computation, semantics and verification of programs, and theoretical issues in artificial intelligence.
Download or read book Computer Science Theory and Applications written by Edward Hirsch and published by Springer. This book was released on 2014-06-02 with total page 407 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the proceedings of the 9th International Computer Science Symposium in Russia, CSR 2014, held in Moscow, Russia, in June 2014. The 27 full papers presented in this volume were carefully reviewed and selected from 76 submissions. In addition the book contains 4 invited lectures. The scope of the proposed topics is quite broad and covers a wide range of areas in theoretical computer science and its applications.
Download or read book Combinatorial Pattern Matching written by Juha Kärkkäinen and published by Springer. This book was released on 2012-06-13 with total page 466 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 23rd Annual Symposium on Combinatorial Pattern Matching, CPM 2012, held in Helsinki, Finland, in July 2012. The 33 revised full papers presented together with 2 invited talks were carefully reviewed and selected from 60 submissions. The papers address issues of searching and matching strings and more complicated patterns such as trees, regular expressions, graphs, point sets, and arrays. The goal is to derive non-trivial combinatorial properties of such structures and to exploit these properties in order to either achieve superior performance for the corresponding computational problems or pinpoint conditions under which searches cannot be performed efficiently. The meeting also deals with problems in computational biology, data compression and data mining, coding, information retrieval, natural language processing, and pattern recognition.
Download or read book Combinatorial Optimization and Graph Algorithms written by Takuro Fukunaga and published by Springer. This book was released on 2017-10-02 with total page 126 pages. Available in PDF, EPUB and Kindle. Book excerpt: Covering network designs, discrete convex analysis, facility location and clustering problems, matching games, and parameterized complexity, this book discusses theoretical aspects of combinatorial optimization and graph algorithms. Contributions are by renowned researchers who attended NII Shonan meetings on this essential topic. The collection contained here provides readers with the outcome of the authors’ research and productive meetings on this dynamic area, ranging from computer science and mathematics to operations research. Networks are ubiquitous in today's world: the Web, online social networks, and search-and-query click logs can lead to a graph that consists of vertices and edges. Such networks are growing so fast that it is essential to design algorithms to work for these large networks. Graph algorithms comprise an area in computer science that works to design efficient algorithms for networks. Here one can work on theoretical or practical problems where implementation of an algorithm for large networks is needed. In two of the chapters, recent results in graph matching games and fixed parameter tractability are surveyed. Combinatorial optimization is an intersection of operations research and mathematics, especially discrete mathematics, which deals with new questions and new problems, attempting to find an optimum object from a finite set of objects. Most problems in combinatorial optimization are not tractable (i.e., NP-hard). Therefore it is necessary to design an approximation algorithm for them. To tackle these problems requires the development and combination of ideas and techniques from diverse mathematical areas including complexity theory, algorithm theory, and matroids as well as graph theory, combinatorics, convex and nonlinear optimization, and discrete and convex geometry. Overall, the book presents recent progress in facility location, network design, and discrete convex analysis.
Download or read book Clustering and Information Retrieval written by Weili Wu and published by Springer Science & Business Media. This book was released on 2003-11-30 with total page 350 pages. Available in PDF, EPUB and Kindle. Book excerpt: Clustering is an important technique for discovering relatively dense sub-regions or sub-spaces of a multi-dimension data distribution. Clus tering has been used in information retrieval for many different purposes, such as query expansion, document grouping, document indexing, and visualization of search results. In this book, we address issues of cluster ing algorithms, evaluation methodologies, applications, and architectures for information retrieval. The first two chapters discuss clustering algorithms. The chapter from Baeza-Yates et al. describes a clustering method for a general metric space which is a common model of data relevant to information retrieval. The chapter by Guha, Rastogi, and Shim presents a survey as well as detailed discussion of two clustering algorithms: CURE and ROCK for numeric data and categorical data respectively. Evaluation methodologies are addressed in the next two chapters. Ertoz et al. demonstrate the use of text retrieval benchmarks, such as TRECS, to evaluate clustering algorithms. He et al. provide objective measures of clustering quality in their chapter. Applications of clustering methods to information retrieval is ad dressed in the next four chapters. Chu et al. and Noel et al. explore feature selection using word stems, phrases, and link associations for document clustering and indexing. Wen et al. and Sung et al. discuss applications of clustering to user queries and data cleansing. Finally, we consider the problem of designing architectures for infor mation retrieval. Crichton, Hughes, and Kelly elaborate on the devel opment of a scientific data system architecture for information retrieval.
Download or read book Clustering and Network Analysis with Biological Applications written by Konstantin Voevodski and published by . This book was released on 2011 with total page 154 pages. Available in PDF, EPUB and Kindle. Book excerpt: Abstract: Clustering and network analysis are important areas of research in Computer Science and other disciplines. Clustering is broadly defined as finding sets of similar objects. It has many applications, such as finding groups of similar buyers given their product preferences, and finding groups of similar proteins given their sequences. Network analysis considers data represented by a collection of nodes (vertices), and edges that link these nodes. The structure of the network is studied to find central nodes, identify nodes that are similar to a particular vertex, and find well-connected groups of vertices. The World Wide Web and online social networks are some of the best studied networks today. Network analysis can also be applied to biological networks where nodes are proteins and edges represent relationships or interactions between them. The size of real-world data sets presents many challenges to computational techniques that interpret them. A classic clustering problem is to divide the data set into groups, given the pairwise distances between the objects. However, computing all the pairwise distances may be infeasible if the data set is very large. In this thesis we consider clustering in a limited information setting where we do not know the distances between the objects in advance, and instead must query them during the execution of the algorithm. We present algorithms that find an accurate clustering in this setting using few queries. The networks that we encounter in practice are quite large as well, making computations on the entire network difficult. In this thesis we present techniques for locally exploring networks, which are efficient but still give meaningful information about the local structure of the graph. We develop several tools for locally exploring a network, and show that they give meaningful results when applied to protein networks.
Download or read book Wireless Communications Networking and Applications written by Qing-An Zeng and published by Springer. This book was released on 2015-10-28 with total page 1265 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is based on a series of conferences on Wireless Communications, Networking and Applications that have been held on December 27-28, 2014 in Shenzhen, China. The meetings themselves were a response to technological developments in the areas of wireless communications, networking and applications and facilitate researchers, engineers and students to share the latest research results and the advanced research methods of the field. The broad variety of disciplines involved in this research and the differences in approaching the basic problems are probably typical of a developing field of interdisciplinary research. However, some main areas of research and development in the emerging areas of wireless communication technology can now be identified. The contributions to this book are mainly selected from the papers of the conference on wireless communications, networking and applications and reflect the main areas of interest: Section 1 - Emerging Topics in Wireless and Mobile Computing and Communications; Section 2 - Internet of Things and Long Term Evolution Engineering; Section 3 - Resource Allocation and Interference Management; Section 4 - Communication Architecture, Algorithms, Modeling and Evaluation; Section 5 - Security, Privacy, and Trust; and Section 6 - Routing, Position Management and Network Topologies.
Download or read book Encyclopedia of Algorithms written by Ming-Yang Kao and published by Springer Science & Business Media. This book was released on 2008-08-06 with total page 1200 pages. Available in PDF, EPUB and Kindle. Book excerpt: One of Springer’s renowned Major Reference Works, this awesome achievement provides a comprehensive set of solutions to important algorithmic problems for students and researchers interested in quickly locating useful information. This first edition of the reference focuses on high-impact solutions from the most recent decade, while later editions will widen the scope of the work. All entries have been written by experts, while links to Internet sites that outline their research work are provided. The entries have all been peer-reviewed. This defining reference is published both in print and on line.
Download or read book Parameterized Algorithms written by Marek Cygan and published by Springer. This book was released on 2015-07-20 with total page 618 pages. Available in PDF, EPUB and Kindle. Book excerpt: This comprehensive textbook presents a clean and coherent account of most fundamental tools and techniques in Parameterized Algorithms and is a self-contained guide to the area. The book covers many of the recent developments of the field, including application of important separators, branching based on linear programming, Cut & Count to obtain faster algorithms on tree decompositions, algorithms based on representative families of matroids, and use of the Strong Exponential Time Hypothesis. A number of older results are revisited and explained in a modern and didactic way. The book provides a toolbox of algorithmic techniques. Part I is an overview of basic techniques, each chapter discussing a certain algorithmic paradigm. The material covered in this part can be used for an introductory course on fixed-parameter tractability. Part II discusses more advanced and specialized algorithmic ideas, bringing the reader to the cutting edge of current research. Part III presents complexity results and lower bounds, giving negative evidence by way of W[1]-hardness, the Exponential Time Hypothesis, and kernelization lower bounds. All the results and concepts are introduced at a level accessible to graduate students and advanced undergraduate students. Every chapter is accompanied by exercises, many with hints, while the bibliographic notes point to original publications and related work.
Download or read book Intelligent Techniques for Warehousing and Mining Sensor Network Data written by Cuzzocrea, Alfredo and published by IGI Global. This book was released on 2009-12-31 with total page 424 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This book focuses on the relevant research theme of warehousing and mining sensor network data, specifically for the database, data warehousing and data mining research communities"--Provided by publisher.
Download or read book Intelligent Multidimensional Data Clustering and Analysis written by Bhattacharyya, Siddhartha and published by IGI Global. This book was released on 2016-11-29 with total page 471 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data mining analysis techniques have undergone significant developments in recent years. This has led to improved uses throughout numerous functions and applications. Intelligent Multidimensional Data Clustering and Analysis is an authoritative reference source for the latest scholarly research on the advantages and challenges presented by the use of cluster analysis techniques. Highlighting theoretical foundations, computing paradigms, and real-world applications, this book is ideally designed for researchers, practitioners, upper-level students, and professionals interested in the latest developments in cluster analysis for large data sets.
Download or read book Computational Science ICCS 2022 written by Derek Groen and published by Springer Nature. This book was released on 2022-06-21 with total page 790 pages. Available in PDF, EPUB and Kindle. Book excerpt: The four-volume set LNCS 13350, 13351, 13352, and 13353 constitutes the proceedings of the 22ndt International Conference on Computational Science, ICCS 2022, held in London, UK, in June 2022.* The total of 175 full papers and 78 short papers presented in this book set were carefully reviewed and selected from 474 submissions. 169 full and 36 short papers were accepted to the main track; 120 full and 42 short papers were accepted to the workshops/ thematic tracks. *The conference was held in a hybrid format Chapter “GPU Accelerated Modelling and Forecasting for Large Time Series” is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.
Download or read book Algorithms and Data Structures written by Frank Dehne and published by Springer. This book was released on 2013-07-11 with total page 550 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 13th Algorithms and Data Structures Symposium, WADS 2013, held in London, ON, Canada, August 2013. The Algorithms and Data Structures Symposium - WADS (formerly "Workshop on Algorithms and Data Structures") is intended as a forum for researchers in the area of design and analysis of algorithms and data structures. The 44 revised full papers presented in this volume were carefully reviewed and selected from 139 submissions. The papers present original research on algorithms and data structures in all areas, including bioinformatics, combinatorics, computational geometry, databases, graphics, and parallel and distributed computing.
Download or read book Comparative Analysis of Classic Clustering Algorithms and Girvan Newman Algorithm for Finding Communities in Social Networks written by Jelena Ljucović and published by . This book was released on 2018 with total page 8 pages. Available in PDF, EPUB and Kindle. Book excerpt: Nowadays finding patterns in large social network datasets is a growing challenge and an important subject of interest. One of current problems in this field is identifying clusters within social networks with large number of nodes. Social network clusters are not necessarily disjoint sets; rather they may overlap and have common nodes, in which case it is more appropriate to designate them as communities. Although many clustering algorithms handle small datasets well, they are usually extremely inefficient on large datasets. This paper shows comparative analysis of frequently used classic graph clustering algorithms and well-known Girvan-Newman algorithm that is used for identification of communities in graphs, which is especially optimized for large datasets. The goal of the paper is to show which of the algorithms give best performances on given dataset. The paper presents real problem of data clustering, algorithms that can be used for its solution, methodology of analysis, results that were achieved and conclusions that were derived.
