1 option
Reasoning Web: Logical Foundation of Knowledge Graph Construction and Query Answering : 12th International Summer School 2016, Aberdeen, UK, September 5-9, 2016, Tutorial Lectures / edited by Jeff Z. Pan, Diego Calvanese, Thomas Eiter, Ian Horrocks, Michael Kifer, Fangzhen Lin, Yuting Zhao.
- Format:
- Book
- Series:
- Computer Science (SpringerNature-11645)
- LNCS sublibrary. Information systems and applications, incl. Internet/Web, and HCI ; SL 3, 9885
- Information Systems and Applications, incl. Internet/Web, and HCI ; 9885
- Language:
- English
- Subjects (All):
- Database management.
- Artificial intelligence.
- Machine theory.
- Information storage and retrieval systems.
- Information technology-Management.
- Data mining.
- Database Management.
- Artificial Intelligence.
- Formal Languages and Automata Theory.
- Information Storage and Retrieval.
- Computer Application in Administrative Data Processing.
- Data Mining and Knowledge Discovery.
- Local Subjects:
- Database Management.
- Artificial Intelligence.
- Formal Languages and Automata Theory.
- Information Storage and Retrieval.
- Computer Application in Administrative Data Processing.
- Data Mining and Knowledge Discovery.
- Physical Description:
- 1 online resource (XIV, 259 pages) : 37 illustrations
- Edition:
- 1st ed. 2017.
- Contained In:
- Springer Nature eBook
- Place of Publication:
- Cham : Springer International Publishing : Imprint: Springer, 2017.
- System Details:
- text file PDF
- Summary:
- This volume contains some lecture notes of the 12th Reasoning Web Summer School (RW 2016), held in Aberdeen, UK, in September 2016. In 2016, the theme of the school was "Logical Foundation of Knowledge Graph Construction and Query Answering". The notion of knowledge graph has become popular since Google started to use it to improve its search engine in 2012. Inspired by the success of Google, knowledge graphs are gaining momentum in the World Wide Web arena. Recent years have witnessed increasing industrial take-ups by other Internet giants, including Facebook's Open Graph and Microsoft's Satori. The aim of the lecture note is to provide a logical foundation for constructing and querying knowledge graphs. Our journey starts from the introduction of Knowledge Graph as well as its history, and the construction of knowledge graphs by considering both explicit and implicit author intentions. The book will then cover various topics, including how to revise and reuse ontologies (schema of knowledge graphs) in a safe way, how to combine navigational queries with basic pattern matching queries for knowledge graph, how to setup a environment to do experiments on knowledge graphs, how to deal with inconsistencies and fuzziness in ontologies and knowledge graphs, and how to combine machine learning and machine reasoning for knowledge graphs.
- Contents:
- Understanding Author Intentions: Test Driven Knowledge Graph Construction
- Inseparability and Conservative Extensions of Description Logic Ontologies: A Survey
- Navigational and Rule-Based Languages for Graph Databases
- LOD Lab: Scalable Linked Data Processing
- Inconsistency-Tolerant Querying of Description Logic Knowledge Bases
- From Fuzzy to Annotated Semantic Web Languages
- Applying Machine Reasoning and Learning in Real World Applications.
- Other Format:
- Printed edition:
- ISBN:
- 978-3-319-49493-7
- 9783319494937
- Access Restriction:
- Restricted for use by site license.
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.