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Titlebook: Reasoning Web: Logical Foundation of Knowledge Graph Construction and Query Answering; 12th International S Jeff Z. Pan,Diego Calvanese,Yut

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發(fā)表于 2025-3-21 20:03:06 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書目名稱Reasoning Web: Logical Foundation of Knowledge Graph Construction and Query Answering
副標(biāo)題12th International S
編輯Jeff Z. Pan,Diego Calvanese,Yuting Zhao
視頻videohttp://file.papertrans.cn/823/822488/822488.mp4
概述Made for students, researchers and practitioners interested in Knowledge Graphs, Question Answering, and Semantic Web.Thoroughly revised tutorials cover logical foundations for constructing and queryi
叢書名稱Lecture Notes in Computer Science
圖書封面Titlebook: Reasoning Web: Logical Foundation of Knowledge Graph Construction and Query Answering; 12th International S Jeff Z. Pan,Diego Calvanese,Yut
描述.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 reuseontologies (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
出版日期Textbook 2017
關(guān)鍵詞artificial intelligence; database systems; description logics; fuzzy logic; graph databases; knowledge gr
版次1
doihttps://doi.org/10.1007/978-3-319-49493-7
isbn_softcover978-3-319-49492-0
isbn_ebook978-3-319-49493-7Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightSpringer International Publishing AG 2017
The information of publication is updating

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Lecture Notes in Computer Sciencehttp://image.papertrans.cn/r/image/822488.jpg
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https://doi.org/10.1007/978-3-319-49493-7artificial intelligence; database systems; description logics; fuzzy logic; graph databases; knowledge gr
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Applying Machine Reasoning and Learning in Real World Applications,rence techniques that nicely complement each other in real-world applications. In this chapter we will present how techniques from machine learning and reasoning can be reconciled and integrated to address large scale problems in the context of (i) transportation in cities of Bologna, Dublin, Miami, Rio and (ii) spend optimisation in finance.
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Understanding Author Intentions: Test Driven Knowledge Graph Construction,ns and show how such understanding can be used in reasoning-based test-driven knowledge graph construction and can help design guidelines for bulk editing, efficient reasoning and increased situational awareness. We will discuss extensively the implications of test driven knowledge graph construction to ontology reasoning.
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Understanding Author Intentions: Test Driven Knowledge Graph Construction,ion, we provide the reader with an overview of the book, as well as a brief introduction of the history and the concept of Knowledge Graph..We will introduce the notions of explicit author intention and implicit author intention, discuss some approaches for understanding each type of author intentio
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