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Reasoning Web: Logical Foundation of Knowledge Graph Construction and Query Answering: 12th International Summer School 2016, Aberdeen, UK, September 5-9, 2016, Tutorial Lectures
Kategorie Beschreibung
036aXA-DE
037beng
087q978-3-319-49492-0
100bPan, Jeff Z. ¬[Hrsg.]¬
104bCalvanese, Diego ¬[Hrsg.]¬
108bEiter, Thomas ¬[Hrsg.]¬
112bHorrocks, Ian ¬[Hrsg.]¬
116bKifer, Michael ¬[Hrsg.]¬
120bLin, Fangzhen ¬[Hrsg.]¬
124bZhao, Yuting ¬[Hrsg.]¬
331 Reasoning Web: Logical Foundation of Knowledge Graph Construction and Query Answering
335 12th International Summer School 2016, Aberdeen, UK, September 5-9, 2016, Tutorial Lectures
410 Cham
412 Springer
425 2017
425a2017
433 Online-Ressource (XIV, 259 p. 37 illus, online resource)
451 Lecture Notes in Computer Science ; 9885
454 Lecture notes in computer science
455 9885
527 Druckausg.ISBN: 978-3-319-49492-0
527 Printed editionISBN: 978-3-319-49492-0
540aISBN 978-3-319-49493-7
700 |UMT
700 |*68-06
700 |68M11
700 |68N17
700 |68P15
700 |68T27
700 |68T30
700 |00B25
700 |UN
700 |COM021000
700b|005.74
700c|QA76.9.D3
750 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
753 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
902s 215898257 RDF <Informatik>
902s 211614815 Terminologische Logik
902s 212000837 OWL <Informatik>
902s 211614815 Terminologische Logik
902s 216791049 Ontologie <Wissensverarbeitung>
902s 215048547 Semantic Web
012 485259079
081 Reasoning Web: Logical Foundation of Knowledge Graph Construction and Query Answering
100 Springer E-Book
125aElektronischer Volltext - Campuslizenz
655e$uhttp://dx.doi.org/10.1007/978-3-319-49493-7
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