Machine Learning in Social Networks (Record no. 176599)
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000 -LEADER | |
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fixed length control field | 03585nam a22005655i 4500 |
001 - CONTROL NUMBER | |
control field | 978-981-33-4022-0 |
003 - CONTROL NUMBER IDENTIFIER | |
control field | DE-He213 |
005 - DATE AND TIME OF LATEST TRANSACTION | |
control field | 20240423125319.0 |
007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION | |
fixed length control field | cr nn 008mamaa |
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
fixed length control field | 201125s2021 si | s |||| 0|eng d |
020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
International Standard Book Number | 9789813340220 |
-- | 978-981-33-4022-0 |
024 7# - OTHER STANDARD IDENTIFIER | |
Standard number or code | 10.1007/978-981-33-4022-0 |
Source of number or code | doi |
050 #4 - LIBRARY OF CONGRESS CALL NUMBER | |
Classification number | Q342 |
072 #7 - SUBJECT CATEGORY CODE | |
Subject category code | UYQ |
Source | bicssc |
072 #7 - SUBJECT CATEGORY CODE | |
Subject category code | COM004000 |
Source | bisacsh |
072 #7 - SUBJECT CATEGORY CODE | |
Subject category code | UYQ |
Source | thema |
082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER | |
Classification number | 006.3 |
Edition number | 23 |
100 1# - MAIN ENTRY--PERSONAL NAME | |
Personal name | Aggarwal, Manasvi. |
Relator term | author. |
Relator code | aut |
-- | http://id.loc.gov/vocabulary/relators/aut |
245 10 - TITLE STATEMENT | |
Title | Machine Learning in Social Networks |
Medium | [electronic resource] : |
Remainder of title | Embedding Nodes, Edges, Communities, and Graphs / |
Statement of responsibility, etc | by Manasvi Aggarwal, M.N. Murty. |
250 ## - EDITION STATEMENT | |
Edition statement | 1st ed. 2021. |
264 #1 - | |
-- | Singapore : |
-- | Springer Nature Singapore : |
-- | Imprint: Springer, |
-- | 2021. |
300 ## - PHYSICAL DESCRIPTION | |
Extent | XI, 112 p. 29 illus., 18 illus. in color. |
Other physical details | online resource. |
336 ## - | |
-- | text |
-- | txt |
-- | rdacontent |
337 ## - | |
-- | computer |
-- | c |
-- | rdamedia |
338 ## - | |
-- | online resource |
-- | cr |
-- | rdacarrier |
347 ## - | |
-- | text file |
-- | |
-- | rda |
490 1# - SERIES STATEMENT | |
Series statement | SpringerBriefs in Computational Intelligence, |
International Standard Serial Number | 2625-3712 |
505 0# - FORMATTED CONTENTS NOTE | |
Formatted contents note | Introduction -- Representations of Networks -- Deep Learning -- Node Representations -- Embedding Graphs -- Conclusions. |
520 ## - SUMMARY, ETC. | |
Summary, etc | This book deals with network representation learning. It deals with embedding nodes, edges, subgraphs and graphs. There is a growing interest in understanding complex systems in different domains including health, education, agriculture and transportation. Such complex systems are analyzed by modeling, using networks that are aptly called complex networks. Networks are becoming ubiquitous as they can represent many real-world relational data, for instance, information networks, molecular structures, telecommunication networks and protein–protein interaction networks. Analysis of these networks provides advantages in many fields such as recommendation (recommending friends in a social network), biological field (deducing connections between proteins for treating new diseases) and community detection (grouping users of a social network according to their interests) by leveraging the latent information of networks. An active and important area ofcurrent interest is to come out with algorithms that learn features by embedding nodes or (sub)graphs into a vector space. These tasks come under the broad umbrella of representation learning. A representation learning model learns a mapping function that transforms the graphs' structure information to a low-/high-dimension vector space maintaining all the relevant properties. . |
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
Topical term or geographic name as entry element | Computational intelligence. |
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
Topical term or geographic name as entry element | Machine learning. |
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
Topical term or geographic name as entry element | Artificial intelligence. |
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
Topical term or geographic name as entry element | Neural networks (Computer science)Â . |
650 14 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
Topical term or geographic name as entry element | Computational Intelligence. |
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
Topical term or geographic name as entry element | Machine Learning. |
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
Topical term or geographic name as entry element | Artificial Intelligence. |
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
Topical term or geographic name as entry element | Mathematical Models of Cognitive Processes and Neural Networks. |
700 1# - ADDED ENTRY--PERSONAL NAME | |
Personal name | Murty, M.N. |
Relator term | author. |
Relator code | aut |
-- | http://id.loc.gov/vocabulary/relators/aut |
710 2# - ADDED ENTRY--CORPORATE NAME | |
Corporate name or jurisdiction name as entry element | SpringerLink (Online service) |
773 0# - HOST ITEM ENTRY | |
Title | Springer Nature eBook |
776 08 - ADDITIONAL PHYSICAL FORM ENTRY | |
Display text | Printed edition: |
International Standard Book Number | 9789813340213 |
776 08 - ADDITIONAL PHYSICAL FORM ENTRY | |
Display text | Printed edition: |
International Standard Book Number | 9789813340237 |
830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE | |
Uniform title | SpringerBriefs in Computational Intelligence, |
-- | 2625-3712 |
856 40 - ELECTRONIC LOCATION AND ACCESS | |
Uniform Resource Identifier | <a href="https://doi.org/10.1007/978-981-33-4022-0">https://doi.org/10.1007/978-981-33-4022-0</a> |
912 ## - | |
-- | ZDB-2-SCS |
912 ## - | |
-- | ZDB-2-SXCS |
942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
Koha item type | eBooks-CSE-Springer |
No items available.