Reasoning Web: Logical Foundation of Knowledge Graph Construction and Query Answering : 12th International Summer School 2016, Aberdeen, UK, September 5-9, 2016, Tutorial Lectures (Information Systems and Applications, incl. Internet/web, and Hci)

個数:
電子版価格
¥10,887
  • 電子版あり

Reasoning Web: Logical Foundation of Knowledge Graph Construction and Query Answering : 12th International Summer School 2016, Aberdeen, UK, September 5-9, 2016, Tutorial Lectures (Information Systems and Applications, incl. Internet/web, and Hci)

  • オンデマンド(OD/POD)版です。キャンセルは承れません。
  • 【入荷遅延について】
    世界情勢の影響により、海外からお取り寄せとなる洋書・洋古書の入荷が、表示している標準的な納期よりも遅延する場合がございます。
    おそれいりますが、あらかじめご了承くださいますようお願い申し上げます。
  • ◆画像の表紙や帯等は実物とは異なる場合があります。
  • ◆ウェブストアでの洋書販売価格は、弊社店舗等での販売価格とは異なります。
    また、洋書販売価格は、ご注文確定時点での日本円価格となります。
    ご注文確定後に、同じ洋書の販売価格が変動しても、それは反映されません。
  • 製本 Paperback:紙装版/ペーパーバック版/ページ数 259 p.
  • 言語 ENG
  • 商品コード 9783319494920
  • DDC分類 006.312

Full Description

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 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.

最近チェックした商品