國立高雄大學圖資館 |

語系: 繁體中文

說明(常見問題)

圖資館首頁

登入

回首頁

切換: 標籤 | MARC模式 | ISBD

Domain-specific knowledge graph cons...

Kejriwal, Mayank.

Domain-specific knowledge graph construction

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Domain-specific knowledge graph constructionby Mayank Kejriwal.
作者:	Kejriwal, Mayank.
出版者:	Cham :Springer International Publishing :2019.
面頁冊數:	xiv, 107 p. :ill., digital ;24 cm.
Contained By:	Springer eBooks
標題:	Expert systems (Computer science)
電子資源:	https://doi.org/10.1007/978-3-030-12375-8
ISBN:	9783030123758$q(electronic bk.)

Domain-specific knowledge graph construction
Kejriwal, Mayank.

Domain-specific knowledge graph construction[electronic resource] /by Mayank Kejriwal. - Cham :Springer International Publishing :2019. - xiv, 107 p. :ill., digital ;24 cm. - SpringerBriefs in computer science,2191-5768. - 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 will describe 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 work would serve as a useful reference, as well as an accessible but rigorous overview of this body of work. The book will present interdisciplinary connections when possible to engage researchers looking for new ideas or synergies. This will allow the book to be marketed in multiple venues and conferences. The book will also appeal to practitioners in industry and data scientists since it will have chapters on both data collection, as well as a chapter on querying and off-the-shelf implementations. The author has, and continues to, present on this topic at large and important conferences. He plans to make the powerpoint he presents available as a supplement to the work. This will draw a natural audience for the book. Some of the reviewers are unsure about his position in the community but that seems to be more a function of his age rather than his relative expertise. I agree with some of the reviewers that the title is a little complicated. I would recommend "Domain Specific Knowledge Graphs".

ISBN: 9783030123758$q(electronic bk.)

Standard No.: 10.1007/978-3-030-12375-8doiSubjects--Topical Terms:

182450
Expert systems (Computer science)

LC Class. No.: QA76.76.E95

Dewey Class. No.: 006.33

Domain-specific knowledge graph construction
LDR:02951nmm a2200337 a 4500 001 553633
003 DE-He213
005 20190304121744.0
006 m d
007 cr nn 008maaau
008 191112s2019 gw s 0 eng d
020 $a 9783030123758$q(electronic bk.)
020 $a 9783030123741$q(paper)
024 7 $a 10.1007/978-3-030-12375-8 $2 doi
035 $a 978-3-030-12375-8
040 $a GP $c GP
041 0 $a eng
050 4 $a QA76.76.E95
072 7 $a UNF $2 bicssc
072 7 $a COM021030 $2 bisacsh
072 7 $a UNF $2 thema
072 7 $a UYQE $2 thema
082 0 4 $a 006.33 $2 23
090 $a QA76.76.E95 $b K28 2019
100 1 $a Kejriwal, Mayank. $3 835025
245 1 0 $a Domain-specific knowledge graph construction $h [electronic resource] / $c by Mayank Kejriwal.
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2019.
300 $a xiv, 107 p. : $b ill., digital ; $c 24 cm.
490 1 $a SpringerBriefs in computer science, $x 2191-5768
520 $a 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 will describe 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 work would serve as a useful reference, as well as an accessible but rigorous overview of this body of work. The book will present interdisciplinary connections when possible to engage researchers looking for new ideas or synergies. This will allow the book to be marketed in multiple venues and conferences. The book will also appeal to practitioners in industry and data scientists since it will have chapters on both data collection, as well as a chapter on querying and off-the-shelf implementations. The author has, and continues to, present on this topic at large and important conferences. He plans to make the powerpoint he presents available as a supplement to the work. This will draw a natural audience for the book. Some of the reviewers are unsure about his position in the community but that seems to be more a function of his age rather than his relative expertise. I agree with some of the reviewers that the title is a little complicated. I would recommend "Domain Specific Knowledge Graphs".
650 0 $a Expert systems (Computer science) $3 182450
650 0 $a Graph databases. $3 835026
650 1 4 $a Data Mining and Knowledge Discovery. $3 275288
650 2 4 $a Information Storage and Retrieval. $3 274190
650 2 4 $a Information Systems Applications (incl. Internet) $3 530743
650 2 4 $a Probability and Statistics in Computer Science. $3 274053
710 2 $a SpringerLink (Online service) $3 273601
773 0 $t Springer eBooks
830 0 $a SpringerBriefs in computer science. $3 559641
856 4 0 $u https://doi.org/10.1007/978-3-030-12375-8
950 $a Computer Science (Springer-11645)