.png){kind=logo}
Stock image for illustration purposes only - book cover, edition or condition may vary.
Semantic, Analytics, Visualization. Enhancing Scholarly Data
. Ed(S): Gonzalez-Beltran, Alejandra; Osborne, Francesco; Peroni, Silvio
€ 65.56
FREE Delivery in Ireland
Description for Semantic, Analytics, Visualization. Enhancing Scholarly Data
Paperback. Editor(s): Gonzalez-Beltran, Alejandra; Osborne, Francesco; Peroni, Silvio. Series: Lecture Notes in Computer Science. Num Pages: 142 pages, 39 black & white illustrations, biography. BIC Classification: UKN; UN; UNF; UNH; UYZG. Category: (G) General (US: Trade). Dimension: 235 x 155. .
This book constitutes the refereed proceedings of the Second International Workshop on Semantics, Analytics, Visualization,- Enhancing Scholarly Data,- SAVE-SD 2016, held in Montreal, QC, Canada, in April 2016.
The 5 full papers, 6 demo and poster papers and 2 position papers, were carefully reviewed and selected from 16 submissions. The papers are organized in two topical sections: "Extracting Knowledge from Research Publications" and "Semantic Technologies for Citation and Topic Analysis".
This book constitutes the refereed proceedings of the Second International Workshop on Semantics, Analytics, Visualization,- Enhancing Scholarly Data,- SAVE-SD 2016, held in Montreal, QC, Canada, in April 2016.
The 5 full papers, 6 demo and poster papers and 2 position papers, were carefully reviewed and selected from 16 submissions. The papers are organized in two topical sections: "Extracting Knowledge from Research Publications" and "Semantic Technologies for Citation and Topic Analysis".
Product Details
Format
Paperback
Publication date
2017
Publisher
Springer International Publishing AG Switzerland
Number of pages
142
Condition
New
Series
Lecture Notes in Computer Science
Number of Pages
153
Place of Publication
Cham, Switzerland
ISBN
9783319536361
SKU
V9783319536361
Shipping Time
Usually ships in 15 to 20 working days
Ref
99-15
Reviews for Semantic, Analytics, Visualization. Enhancing Scholarly Data