Graph Data Management by Sherif Sakr
Graphs are a powerful tool for representing and understanding objects and their relationships in various application domains. The growing popularity of graph databases has generated data management problems that include finding efficient techniques for compressing large graph databases and suitable techniques for visualizing, browsing, and navigating large graph databases. Graph Data Management: Techniques and Applications is a central reference source for different data management techniques for graph data structures and their application. This book discusses graphs for modeling complex structured and schemaless data from the Semantic Web, social networks, protein networks, chemical compounds, and multimedia databases and offers essential research for academics working in the interdisciplinary domains of databases, data mining, and multimedia technology.-
Intelligent Multidimensional Data Clustering and Analysis
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Emerging Methods in Predictive Analytics
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Innovative Techniques and Applications of Entity Resolution
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Data Mining and Analysis in the Engineering Field
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XML Data Mining
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Design, Performance, and Analysis of Innovative Information Retrieval
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Intelligent Techniques for Data Analysis in Diverse Settings
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Handbook of Research on Big Data Management and Applications
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Data Mining Trends and Applications in Criminal Science and Investigations
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Web Usage Mining Techniques and Applications Across Industries
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Collaborative Filtering Using Data Mining and Analysis
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Social Media Data Extraction and Content Analysis
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Mobile Technologies for Activity-Travel Data Collection and Analysis
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Web Semantics for Textual and Visual Information Retrieval
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Knowledge Discovery Practices and Emerging Applications of Data Mining
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Emerging Trends in the Development and Application of Composite Indicators
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Web Data Mining and the Development of Knowledge-Based Decision Support Systems
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Data Mining in Public and Private Sectors
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Innovative Document Summarization Techniques
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Data Science and Simulation in Transportation Research
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Data Visualization and Statistical Literacy for Open and Big Data
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Biologically-Inspired Techniques for Knowledge Discovery and Data Mining
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Data Mining in Dynamic Social Networks and Fuzzy Systems
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Advancing Cloud Database Systems and Capacity Planning with Dynamic Applications
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Innovative Approaches of Data Visualization and Visual Analytics
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Advanced Database Query Systems
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Exploring the Convergence of Big Data and the Internet of Things
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Text Mining Techniques for Healthcare Provider Quality Determination
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Big Data Management, Technologies, and Applications
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Ethical Data Mining Applications for Socio-Economic Development
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Managing and Processing Big Data in Cloud Computing
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Handbook of Research on Innovative Database Query Processing Techniques
Eric Pardede is a lecturer at La Trobe University, Melbourne. He has authored more than 30 research papers that were published in international journals and conference proceedings. His current research areas are XML databases, community-built databases, and health informatics.
| SKU | Unavailable |
| ISBN 13 | 9781613500538 |
| ISBN 10 | 161350053X |
| Title | Graph Data Management |
| Author | Sherif Sakr |
| Series | Advances In Data Mining And Database Management |
| Condition | Unavailable |
| Binding Type | Hardback |
| Publisher | Business Science Reference |
| Year published | 2011-08-31 |
| Number of pages | 346 |
| Cover note | Book picture is for illustrative purposes only, actual binding, cover or edition may vary. |
| Note | Unavailable |