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Mining Heterogeneous Information Networks

Author : Yizhou Sun
language : en
Publisher: Morgan & Claypool Publishers
Release Date : 2012-08-15

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Real-world physical and abstract data objects are interconnected, forming gigantic, interconnected networks. By structuring these data objects and interactions between these objects into multiple types, such networks become semi-structured heterogeneous information networks. Most real-world applications that handle big data, including interconnected social media and social networks, scientific, engineering, or medical information systems, online e-commerce systems, and most database systems, can be structured into heterogeneous information networks. Therefore, effective analysis of large-scale heterogeneous information networks poses an interesting but critical challenge. In this book, we investigate the principles and methodologies of mining heterogeneous information networks. Departing from many existing network models that view interconnected data as homogeneous graphs or networks, our semi-structured heterogeneous information network model leverages the rich semantics of typed nodes and links in a network and uncovers surprisingly rich knowledge from the network. This semi-structured heterogeneous network modeling leads to a series of new principles and powerful methodologies for mining interconnected data, including: (1) rank-based clustering and classification; (2) meta-path-based similarity search and mining; (3) relation strength-aware mining, and many other potential developments. This book introduces this new research frontier and points out some promising research directions. Table of Contents: Introduction / Ranking-Based Clustering / Classification of Heterogeneous Information Networks / Meta-Path-Based Similarity Search / Meta-Path-Based Relationship Prediction / Relation Strength-Aware Clustering with Incomplete Attributes / User-Guided Clustering via Meta-Path Selection / Research Frontiers

Social Sensing

Author : Dong Wang
language : en
Publisher: Morgan Kaufmann
Release Date : 2015-04-17

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Increasingly, human beings are sensors engaging directly with the mobile Internet. Individuals can now share real-time experiences at an unprecedented scale. Social Sensing: Building Reliable Systems on Unreliable Data looks at recent advances in the emerging field of social sensing, emphasizing the key problem faced by application designers: how to extract reliable information from data collected from largely unknown and possibly unreliable sources. The book explains how a myriad of societal applications can be derived from this massive amount of data collected and shared by average individuals. The title offers theoretical foundations to support emerging data-driven cyber-physical applications and touches on key issues such as privacy. The authors present solutions based on recent research and novel ideas that leverage techniques from cyber-physical systems, sensor networks, machine learning, data mining, and information fusion. Offers a unique interdisciplinary perspective bridging social networks, big data, cyber-physical systems, and reliability Presents novel theoretical foundations for assured social sensing and modeling humans as sensors Includes case studies and application examples based on real data sets Supplemental material includes sample datasets and fact-finding software that implements the main algorithms described in the book

Graph Based Social Media Analysis

Author : Ioannis Pitas
language : en
Publisher: CRC Press
Release Date : 2016-04-19

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Focused on the mathematical foundations of social media analysis, Graph-Based Social Media Analysis provides a comprehensive introduction to the use of graph analysis in the study of social and digital media. It addresses an important scientific and technological challenge, namely the confluence of graph analysis and network theory with linear algebra, digital media, machine learning, big data analysis, and signal processing. Supplying an overview of graph-based social media analysis, the book provides readers with a clear understanding of social media structure. It uses graph theory, particularly the algebraic description and analysis of graphs, in social media studies. The book emphasizes the big data aspects of social and digital media. It presents various approaches to storing vast amounts of data online and retrieving that data in real-time. It demystifies complex social media phenomena, such as information diffusion, marketing and recommendation systems in social media, and evolving systems. It also covers emerging trends, such as big data analysis and social media evolution. Describing how to conduct proper analysis of the social and digital media markets, the book provides insights into processing, storing, and visualizing big social media data and social graphs. It includes coverage of graphs in social and digital media, graph and hyper-graph fundamentals, mathematical foundations coming from linear algebra, algebraic graph analysis, graph clustering, community detection, graph matching, web search based on ranking, label propagation and diffusion in social media, graph-based pattern recognition and machine learning, graph-based pattern classification and dimensionality reduction, and much more. This book is an ideal reference for scientists and engineers working in social media and digital media production and distribution. It is also suitable for use as a textbook in undergraduate or graduate courses on digital media, social media, or social networks.

Advances In Information Retrieval

Author : Maarten de Rijke
language : en
Publisher: Springer
Release Date : 2014-03-24

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This book constitutes the proceedings of the 36th European Conference on IR Research, ECIR 2014, held in Amsterdam, The Netherlands, in April 2014. The 33 full papers, 50 poster papers and 15 demonstrations presented in this volume were carefully reviewed and selected from 288 submissions. The papers are organized in the following topical sections: evaluation, recommendation, optimization, semantics, aggregation, queries, mining social media, digital libraries, efficiency, and information retrieval theory. Also included are 3 tutorial and 4 workshop presentations.

Provenance Data In Social Media

Author : Geoffrey Barbier
language : en
Publisher: Morgan & Claypool Publishers
Release Date : 2013-05-01

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Social media shatters the barrier to communicate anytime anywhere for people of all walks of life. The publicly available, virtually free information in social media poses a new challenge to consumers who have to discern whether a piece of information published in social media is reliable. For example, it can be difficult to understand the motivations behind a statement passed from one user to another, without knowing the person who originated the message. Additionally, false information can be propagated through social media, resulting in embarrassment or irreversible damages. Provenance data associated with a social media statement can help dispel rumors, clarify opinions, and confirm facts. However, provenance data about social media statements is not readily available to users today. Currently, providing this data to users requires changing the social media infrastructure or offering subscription services. Taking advantage of social media features, research in this nascent field spearheads the search for a way to provide provenance data to social media users, thus leveraging social media itself by mining it for the provenance data. Searching for provenance data reveals an interesting problem space requiring the development and application of new metrics in order to provide meaningful provenance data to social media users. This lecture reviews the current research on information provenance, explores exciting research opportunities to address pressing needs, and shows how data mining can enable a social media user to make informed judgements about statements published in social media. Table of Contents: Information Provenance in Social Media / Provenance Attributes / Provenance via Network Information / Provenance Data

Medizinische Informatik Und Bioinformatik

Author : Martin Dugas
language : de
Publisher: Springer-Verlag
Release Date : 2013-03-11

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Das Buch bietet sowohl Medizinern und Biologen als auch Informatikern einen umfassenden und verständlichen Einstieg in die Medizinische Informatik und Bioinformatik. Die Darstellung der Themen ist abgestimmt auf die Studieninhalte dieser neuen Fachrichtungen. In den ersten Kapiteln werden die Grundbegriffe der Medizin (z.B. Anatomie, Biochemie, Physiologie, Genetik, Gesundheitswesen) und der Informatik (z.B. Algorithmen, Datenbanken, Internet, Software Engineering) erläutert. Dies ermöglicht dem Informatiker bzw. Mediziner einen schnellen Zugang zum jeweils komplementären Fachgebiet. In den folgenden Kapiteln werden alle relevanten Themen der Medizinischen Informatik (z.B. Krankenhausinformationssysteme, PACS, Datenschutz, ICD, DRG, Computer-based-Training) und der Bioinformatik (z.B. Sequenzanalyse, Gen-Datenbanken, Proteomics, Genomics, Genexpressionsanalyse) anschaulich dargestellt.

Alles Leben Ist Probleml Sen

Author : Karl R. Popper
language : de
Release Date : 2003

PDF Download Alles Leben Ist Probleml Sen Books For free written by Karl R. Popper and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003 with Civilization, Modern categories.