Domain-Specific Knowledge Graph Construction (SpringerBriefs in Computer Science)

The vast amounts of ontologically unstructured information on the Web, including HTML, XML and JSON documents, natural language documents, tweets, blogs, markups, and even structured documents like CSV tables, all contain useful knowledge that can present a tremendous advantage to the Artificial Intelligence community if extracted robustly, efficiently and semi-automatically as knowledge graphs. Domain-specific Knowledge Graph Construction (KGC) is an active research area that has recently witnessed impressive advances due to machine learning techniques like deep neural networks and word embeddings. This book will synthesize Knowledge Graph Construction over Web Data in an engaging and accessible manner.

The book describes a timely topic for both early -and mid-career researchers. Every year, more papers continue to be published on knowledge graph construction, especially for difficult Web domains. This book serves as a useful reference, as well as anaccessible but rigorous overview of this body of work. The book presents interdisciplinary connections when possible to engage researchers looking for new ideas or synergies. The book also appeals to practitioners in industry and data scientists since it has chapters on both data collection, as well as a chapter on querying and off-the-shelf implementations.

ASIN ‏ : ‎ B07PGPQQ2K
Publisher ‏ : ‎ Springer
Accessibility ‏ : ‎ Learn more
Publication date ‏ : ‎ March 4, 2019
Edition ‏ : ‎ 1st ed. 2019
Language ‏ : ‎ English
File size ‏ : ‎ 11.5 MB
Screen Reader ‏ : ‎ Supported
Enhanced typesetting ‏ : ‎ Enabled
X-Ray ‏ : ‎ Not Enabled
Word Wise ‏ : ‎ Not Enabled
Print length ‏ : ‎ 227 pages
ISBN-13 ‏ : ‎ 978-3030123758
Page Flip ‏ : ‎ Enabled
Part of series ‏ : ‎ SpringerBriefs in Computer Science
Best Sellers Rank: #3,446,279 in Kindle Store (See Top 100 in Kindle Store) #204 in Data Storage & Retrieval #341 in Network Storage & Retrieval Administration #534 in Mathematical & Statistical
Customer Reviews: 3.3 3.3 out of 5 stars (4) var dpAcrHasRegisteredArcLinkClickAction; P.when('A', 'ready').execute(function(A) { if (dpAcrHasRegisteredArcLinkClickAction !== true) { dpAcrHasRegisteredArcLinkClickAction = true; A.declarative( 'acrLink-click-metrics', 'click', { "allowLinkDefault": true }, function (event) { if (window.ue) { ue.count("acrLinkClickCount", (ue.count("acrLinkClickCount") || 0) + 1); } } ); } }); P.when('A', 'cf').execute(function(A) { A.declarative('acrStarsLink-click-metrics', 'click', { "allowLinkDefault" : true }, function(event){ if(window.ue) { ue.count("acrStarsLinkWithPopoverClickCount", (ue.count("acrStarsLinkWithPopoverClickCount") || 0) + 1); } }); });