Emergent Semantics: 1st Edition (Hardback) book cover

Emergent Semantics

1st Edition

By Philippe Cudre-Mauroux

EPFL Press

240 pages

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pub: 2008-10-09
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Description

Peer-to-peer systems are evolving with new information-system architectures, leading to the idea that the principles of decentralization and self-organization will offer new approaches in informatics, especially for systems that scale with the number of users or for which central authorities do not prevail. This book describes a new way of building global agreements (semantic interoperability) based only on decentralized, self-organizing interactions.

Table of Contents

Preface

Chapter 1 Introduction

1.1 On Syntax, Semantics and Syntactic Semantics

1.2 Emergent Semantics

in Distributed Information Systems

1.3 Scope of the Research

1.4 What this Book is not about

1.5 Outline

1.6 Contributions

Chapter 2 On Integrating Data

in the Internet Era

2.1 Federated Databases

2.2 XML, RDF and the Semantic Web

Chapter 3 Peer-to-Peer Information Management

3.1 From unstructured to structured P2P Systems

3.2 Peer Data Management

Chapter 4 Semantic Gossiping

4.1 On Uncertain Schema Mappings

in Decentralized Settings

4.1.1 Mapping Completeness

4.1.2 Mapping Soundness

4.2 The Model

4.2.1 The Data Model

4.2.2 The Network Model

4.3 Overview

4.4 Syntactic Similarity

4.5 Semantic Similarity

4.5.1 Cycle Analysis

4.5.2 Result Analysis

4.6 Gossiping Algorithm

4.7 Case Study

4.8 Related Work

4.9 Conclusions

Chapter 5 Self-Repairing Semantic Networks

5.1 Experimental setup

5.2 Cycle Analysis

5.3 Result Analysis

5.4 Combined Analysis

5.5 Related Work

5.6 Conclusions

Chapter 6 Probabilistic Message Passing

6.1 Introduction

6.2 Problem Definition

6.2.1 An Introductory Example

6.3 Modeling PDMSs as Factor-Graphs

6.3.1 A Quick Reminder on Factor-Graphs

and Message Passing Schemes

6.3.2 On Factor-Graphs

in Undirected PDMSs

6.3.3 On Factor-Graphs in Directed PDMSs

with Containment Mappings

6.4 Embedded Message Passing

6.4.1 On Feedback Variables

in PDMS Factor-Graphs

6.4.2 On Cycles in PDMS Factor-Graphs

6.4.3 Embedded Message Passing Schedules

6.4.4 Prior Belief Updates

6.4.5 Introductory Example Revisited

6.5 Performance Evaluation

6.5.1 Performance Analyses

6.5.2 Performance Evaluation

on Random PDMS Networks

6.5.3 Applying Message Passing

on Real-World Schemas

6.6 Conclusions

Chapter 7 Analyzing Semantic Interoperability in the Large

7.1 Introduction

7.2 The Model

7.2.1 The Peer-to-Peer Model

7.2.2 The Peer-to-Schema Model

7.2.3 The Schema-to-Schema Model

7.3 Semantic Interoperability In the Large

7.3.1 Semantic Connectivity

7.4 A Necessary Condition

for Semantic Interoperability

7.4.1 Undirected Model

7.4.2 Directed Model

7.5 Semantic Component Size

7.6 Weighted Graphs

7.6.1 Connectivity Indicator

7.6.2 Giant Component Size

7.7 Semantic Interoperability

in a Bioinformatic Database Network

7.7.1 The Sequence Retrieval System (SRS)

7.7.2 Graph analysis of an SRS repository

7.7.3 Applying the Heuristics

to the SRS Graph

7.7.4 Generating a Graph with

a given Power-Law Degree Distribution

7.8 Use Case Scenarios

7.9 Conclusions

Chapter 8 GridVine:Building Internet-Scale

Semantic Overlay Networks

8.1 Introduction

8.2 Overview of our Approach

8.2.1 Data Independence

8.2.2 Decentralized Semantics

8.3 The P-Grid P2P System

8.4 Semantic Support

8.4.1 Metadata Storage

8.4.2 Schema Definition And Storage

8.5 Resolving Queries in GridVine

8.5.1 Resolving Atomic Queries

8.5.2 Resolving Conjunctive Queries

8.6 Semantic Interoperability

8.6.1 Schema Inheritance

8.6.2 Semantic Gossiping

8.7 Implementation

8.7.1 Architectural Overview

8.7.2 Querying

8.7.3 Query Reformulation

8.7.4 Experimental Evaluation

8.8 Related Work

8.9 Conclusions

Chapter 9 PicShark: Sharing Semi-Structured Annotations

in the Large

9.1 Introduction.

9.2 Sharing Semi-Structured Metadata

9.2.1 On Semi-Structured Metadata

9.2.2 On the Difficulty

of Sharing Semi-Structured Metadata

9.2.3 Opportunities for Reducing

Metadata Scarcity Collaboratively

9.3 Formal Model

9.3.1 Metadata Entropy

9.4 Recontextualizing Semi-Structured Metadata

9.4.1 Exporting Local Metadata

through Data Indexing

9.4.2 Dealing with Metadata Incompleteness

through Intra-Community Metadata

Imputation

9.4.3 Dealing with Metadata Heterogeneity

through Pairwise Schema Mappings

9.4.4 Dealing with Metadata Incompleteness

through Inter-Community Metadata

Propagation

9.4.5 Possible Answers and User Feedback

9.5 PicShark: Sharing Annotated Pictures

in the Large

9.5.1 Information Extraction in PicShark

9.5.2 Performance Evaluation

9.6 Related Work

9.7 Conclusions

Chapter 10 idMesh: Graph-Based Disambiguation

of Online Identities

10.1 Introduction

10.2 Contributions and Outline

10.3 Related Work

10.4 Problem Definition

10.5 idMesh Constructs

10.6 Making Sense of It

10.6.1 An Introductory Example

10.6.2 Deriving a Factor-Graph

to Retrieve Equivalent Identities

10.6.3 Deriving a Factor-Graph

to Retrieve Up-to-date Identities

10.6.4 Query Answering

10.7 System Perspective

10.7.1 Architectural Overview

10.7.2 Distributed Probabilistic Inference

10.8 Performance Evaluation

10.8.1 Performance of the Inference Network

10.8.2 Scale-Up

10.9 Conclusions

Chapter 11 Conclusions

List of Frequently Used Symbols and Abbreviations

Bibliography

Subject Categories

BISAC Subject Codes/Headings:
COM059000
COMPUTERS / Computer Engineering
COM060000
COMPUTERS / Internet / General