1 option
Semantic search for novel information / Michael Farber.
- Format:
- Book
- Author/Creator:
- Farber, Michael, author.
- Series:
- Studies on the Semantic Web ; Volume 031.
- Studies on the Semantic Web ; Volume 031
- Language:
- English
- Subjects (All):
- Semantic computing.
- Semantic Web.
- Physical Description:
- 1 online resource (214 pages).
- Edition:
- 1st ed.
- Place of Publication:
- Berlin, [Germany] : IOS Press, 2017.
- Summary:
- In this book, new approaches are presented for detecting and extracting simultaneously relevant and novel information from unstructured text documents.A major contribution of these approaches is that the information already provided and the extracted information are modeled semantically.
- Contents:
- Title Page
- Abstract
- Acknowledgements
- Contents
- List of Figures
- List of Tables
- List of Listings
- Introduction
- Motivation
- Problem Statement
- Research Questions
- Contribution of the Thesis
- Published Results
- Readers' Guide
- Foundations
- Semantic Web Technologies
- The Vision of the Semantic Web
- RDF and SPARQL
- Knowledge Graph
- Information Extraction, Machine Learning, Information Retrieval, and Data Quality
- Information Extraction
- Machine Learning
- Information Retrieval
- Data Quality
- State-of-the-Art
- Statistical Search for Relevant Information
- Temporal Information Retrieval
- Trend Detection
- Semantic Search for Relevant Information
- Semantic Search for Relevant Entities
- Semantic Search for Relevant Statements
- Semantic Search for Relevant Events
- Statistical Search for Relevant, Novel Information
- Characteristics of Statistical Search for Relevant, Novel Information
- Evaluations and Data Sets
- Approaches to the Statistical Search for Relevant, Novel Information
- Semantic Search for Relevant, Novel Information
- Semantic Search for Novel Entities
- Semantic Search for Novel Statements
- Semantic Search for Novel Events
- The Suitability of Knowledge Graphs for Semantic Novelty Detection
- Selection of Knowledge Graphs
- Key Statistics of Selected Knowledge Graphs
- Related Work
- Number of Triples and Statements
- Classes and Domains
- Relations and Predicates
- Instances and Entities
- Subjects and Objects
- Summary of Key Statistics
- Completeness and Timeliness of Selected Knowledge Graphs
- Gold Standard
- Completeness
- Timeliness
- Discussion
- Conclusions
- Emerging Entity Detection
- Entity Linking Challenges Arising from Missing Entities and Missing Surface Forms
- Overview of Entity Linking Challenges.
- Challenges in the Wild
- Summary of Findings
- Approach: Emerging Entity Detection
- The Approach
- Evaluation Results
- Challenge 1: Linking to in-KG Entities via Known Surface Forms
- Challenge 2: Linking to in-KG Entities via Unknown Surface Forms
- Challenge 3: Linking to Out-of-KG Entities via Known Surface Forms
- Challenge 4: Linking to Out-of-KG Entities via Unkown Surface Forms
- Novel Statement Extraction
- Measuring Semantic Novelty of Statements
- The Novel Statement Extraction System
- Textual Triple Extraction
- KG Linking
- Novelty Detection
- Evaluation 1: CrunchBase
- Data Used
- Evaluation Setting
- Evaluation 2: DBpedia
- The Baseline Approach and its Evaluation Results
- Evaluation Results of Our Approach
- Summary
- Limitations
- Outlook
- Appendix
- Supplementary Material
- Bibliography.
- Notes:
- Includes bibliographical references.
- Description based on online resource; title from PDF title page (ebrary, viewed October 19, 2017).
- Description based on publisher supplied metadata and other sources.
- ISBN:
- 1-61499-775-6
- OCLC:
- 1004378038
The Penn Libraries is committed to describing library materials using current, accurate, and responsible language. If you discover outdated or inaccurate language, please fill out this feedback form to report it and suggest alternative language.