Transactions on large-scale data- and knowledge-centered systems XLV : special issue on data management and knowledge extraction in digital ecosystems /

Transactions on large-scale data- and knowledge-centered systems XLV : special issue on data management and knowledge extraction in digital ecosystems /

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Bibliographic Details
Imprint:Berlin, Germany : Springer, 2020.
Description:1 online resource
Language:English
Series:Lecture notes in computer science ; 12390
Lecture notes in computer science ; 12390.
Subject:
Data mining.
Database management.
Machine learning.
Data mining.
Application software.
Computer networks.
Database management.
Machine learning.
Electronic books.
Format: E-Resource Book
URL for this record:http://pi.lib.uchicago.edu/1001/cat/bib/12607888
Hidden Bibliographic Details
Varying Form of Title:Transactions on large-scale data- and knowledge-centered systems 45
Special issue on data management and knowledge extraction in digital ecosystems
Other authors / contributors:Hameurlain, Abdelkader.
Tjoa, A Min.
Chbeir, Richard.
Manolopoulos, Yannis, 1957-
Ishikawa, Hiroshi, 1956-
Ilarri, Sergio.
Papadopoulos, Apostolos.
ISBN:9783662623084
3662623080
3662623072
9783662623077
Notes:Includes author index.
Online resource; title from PDF title page (SpringerLink, viewed November 5, 2020).
Summary:The LNCS journal Transactions on Large-Scale Data- and Knowledge-Centered Systems focuses on data management, knowledge discovery, and knowledge processing, which are core and hot topics in computer science. Since the 1990s, the Internet has become the main driving force behind application development in all domains. An increase in the demand for resource sharing (e.g., computing resources, services, metadata, data sources) across different sites connected through networks has led to an evolution of data- and knowledge-management systems from centralized systems to decentralized systems enabling large-scale distributed applications providing high scalability. This, the 45th issue of Transactions on Large-Scale Data- and Knowledge-Centered Systems, contains eight revised selected regular papers. Topics covered include data analysis, information extraction, blockchains, and big data.
Other form:Print version: 3662623072 9783662623077
Standard no.:10.1007/978-3-662-62308-4
10.1007/978-3-662-62
Table of Contents:
  • Intro
  • Preface
  • Organization
  • Contents
  • Interoperable Data Extraction and Analytics Queries over Blockchains
  • 1 Introduction
  • 2 Background
  • 2.1 Blockchains
  • 2.2 Blockchain Databases
  • 3 Motivation and Problem Description
  • 4 Abstract Data Model
  • 4.1 Assets
  • 4.2 Participants
  • 4.3 Transactions
  • 5 Datachain
  • 5.1 Users
  • 5.2 Data Management Operations
  • 5.3 Query Interface
  • 6 Evaluation
  • 6.1 Testbed
  • 6.2 Experiments
  • 7 Related Work
  • 8 Conclusion and Future Work
  • References
  • Exploiting Twitter for Informativeness Classification in Disaster Situations
  • 1 Introduction
  • 2 Systematic Disaster Data Analysis
  • 2.1 Temporal Dimension
  • 2.2 Spatial Dimension
  • 2.3 Linguistic Dimension
  • 2.4 Source Dimension
  • 2.5 Event Similarity
  • 2.6 Tweet Similarity
  • 2.7 Summary of Outcomes of Our Data Analysis
  • 3 Classification Approach
  • 3.1 Dataset
  • 3.2 Preprocessing and Feature Extraction
  • 3.3 Automatic Feature Evaluation
  • 3.4 Training and Testing the Classifier
  • 4 Evaluation
  • 4.1 Deep-Small Experiments (DS)
  • 4.2 Broad-Small Experiments (BS)
  • 4.3 Broad-Large Experiments (BL)
  • 4.4 Interpretation of Evaluation
  • 4.5 Classification Performance
  • 5 Related Work
  • 6 Summary and Outlook
  • References
  • COTILES: Leveraging Content and Structure for Evolutionary Community Detection
  • 1 Introduction
  • 2 Preliminaries
  • 2.1 Basic Concepts
  • 2.2 The TILES Algorithm
  • 3 COTILES for Community Detection
  • 3.1 Label Management in COTILES
  • 3.2 COTILES Description
  • 3.3 Tuning COTILES
  • 4 Evaluation
  • 4.1 Experimental Setup
  • 4.2 Structural Analysis
  • 4.3 Content-Based Analysis
  • 4.4 Qualitative Results
  • 5 Related Work
  • 5.1 Structure-Based Methods
  • 5.2 Content-Based Methods
  • 5.3 Combined Methods
  • 5.4 Categorizing Related Methods
  • 6 Conclusions
  • References
  • A Weighted Feature-Based Image Quality Assessment Framework in Real-Time
  • 1 Introduction
  • 1.1 Motivating Scenario
  • 2 Related Work
  • 3 Contributions
  • 4 Definitions
  • 4.1 Data Model
  • 4.2 Data Manipulation Functions
  • 4.3 Image Quality Methods Background
  • 5 Data Quality
  • 5.1 Perceptual Coherence
  • 5.2 Semantic Coherence Measure
  • 5.3 Image Score
  • 6 Proposed Framework
  • 6.1 Stream Processing Module
  • 6.2 Back-End Module
  • 7 Experiments
  • 7.1 Test 1: Evaluation of Image Quality Affected by a Manipulation Function
  • 7.2 Test 2: Evaluation of Apache Storm Performance in Real-Time
  • 8 Conclusion
  • References
  • Sharing Knowledge in Digital Ecosystems Using Semantic Multimedia Big Data
  • 1 Introduction
  • 2 Related Works
  • 3 The Proposed Model
  • 3.1 Ontological Model Formalization
  • 3.2 Property-Based Graph Model Formalization
  • 3.3 Semantic Multimedia Big Data Population
  • 4 A Case Study for Sharing Knowledge
  • 5 Conclusion and Future Works
  • References

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