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Community Search over Big Graphs

, biological, collaboration, and communication networks. Recently, community search over graphs has attracted significantly increasing attention;

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Graph-Based Social Media Analysis

foundations coming from linear algebra, algebraic graph analysis, graph clustering, community detection, graph matching, web search based on ranking;

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Searching and Ranking in Entity-Relationship Graphs

would have to be exploited by expressive search techniques that go beyond today's keyword search paradigm. This work proposes a wide variety;

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Graph-Powered Machine Learning

among terms so you can make accurate search recommendations or locating individuals within a social network who have similar interests, are;

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Graph Mining

HITS algorithm for ranking web search results. Finally, we conclude with a survey of tools and observations from related fields like sociology;

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Baby Shark's Big Show: The Search for Toothy!

Het boek 'Baby Shark's Big Show: The Search for Toothy!' koop je bij bookspot.nl, nu voor 13.68!;

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Structured Search for Big Data

The WWW era made billions of people dramatically dependent on the progress of data technologies, out of which Internet search and Big;

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Graph Sampling

various breadth- or depth-first non-exhaustive search algorithms are applied to obtain compressed views of large often dynamic graphs. Graph;

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Graph-Based Representations in Pattern Recognition

of graphs; topology; graph representations, segmentation and shape; and search in graphs.;

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Algorithms & Data Structures

algorithm, a direct search algorithm is proposed for minimizing an arbitrary function, etc. The following nine chapters present generative;

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Big Data Analytics for Large-Scale Multimedia Search

sections. Big Data Analytics for Large-Scale Multimedia Search covers: representation learning, concept and event-based video search in large;

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Biomedical Data Management and Graph Online Querying

This book constitutes the refereed proceedings of the two International Workshops on Big-Graphs Online Querying, Big-O(Q) 2015, and Data;

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Graph Algorithms

by covering basic material, including graphs and shortest paths, trees, depth-first-search and breadth-first search. The main part of the;

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Graph Algorithms

by covering basic material, including graphs and shortest paths, trees, depth-first-search and breadth-first search. The main part of the;

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Automata, Graphs and Logic

benefit to the students, teachers and research community.;

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Java 9 Data Structures and Algorithms

, this book illustrates the impact of new features on data structures * Gain exposure to important concepts such as Big-O Notation and Dynamic;

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Big Data Analytics and Knowledge Discovery

This book constitutes the refereed proceedings of the 21st International Conference on Big Data Analytics and Knowledge Discovery, DaWaK;

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Similarity Search and Applications

This book constitutes the proceedings of the 9th International Conference on Similarity Search and Applications, SISAP 2016, held in Tokyo;

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Spark GraphX in Action

introduction to graph elements, which are needed to build big data graphs. Then, it explores the problems and possibilities of graph algorithm;

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Combinatorial Optimization and Applications

; Search, Facility and Graphs; Geometric Problem; Sensors, Vehicles and Graphs; and Graph Problems. Due to the Corona pandemic this event;

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Mathematics of Big Data

The first book to present the common mathematical foundations of big data analysis across a range of applications and technologies. Today;

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Big Data - BigData 2019

of Big Data; Big Data Search and Mining; Big Data for Enterprise, Government and Society.;

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Advances in Big Data Analytics

Tools Algorithms for Big Data Big Data Management and Frameworks Big Data Search and Mining Methods Security and Privacy in the Era of Big;

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Reasoning Web: Logical Foundation of Knowledge Graph Construction and Query Answering

become popular since Google started to use it to improve its search engine in 2012. Inspired by the success of Google, knowledge graphs are;

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Knowledge Graphs and Big Data Processing

This open access book is part of the LAMBDA Project (Learning, Applying, Multiplying Big Data Analytics), funded by the European Union, GA;

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Database Systems for Advanced Applications

processing and optimization; search and information retrieval; string and sequence processing; stream date processing; graph and network data;

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Database Systems for Advanced Applications

and optimization; search and information retrieval; string and sequence processing; stream date processing; graph and network data processing;

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