Symbols (Record no. 15210)

MARC details
000 -LEADER
fixed length control field 03518nam a2200373Ia 4500
000 - LEADER
fixed length control field 04050nam a22004095i 4500
001 - CONTROL NUMBER
control field 978-3-031-26809-0
003 - CONTROL NUMBER IDENTIFIER
control field DE-He213
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20240319120858.0
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 230731s2023 sz | s |||| 0|eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9783031268090
-- 978-3-031-26809-0
082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 6.35
100 ## - MAIN ENTRY--PERSONAL NAME
Personal name Sproat, Richard.
9 (RLIN) 31389
245 ## - TITLE STATEMENT
Title Symbols
Statement of responsibility, etc. by Richard Sproat.
Medium [electronic resource] :
250 ## - EDITION STATEMENT
Edition statement 1st ed. 2023.
260 ## - PUBLICATION, DISTRIBUTION, ETC.
Place of publication, distribution, etc. Cham
Name of publisher, distributor, etc. Springer Nature Switzerland
Date of publication, distribution, etc. 2023
300 ## - PHYSICAL DESCRIPTION
Extent XIII, 235 p. 91 illus., 57 illus. in color.
Other physical details online resource.
520 ## - SUMMARY, ETC.
Summary, etc. For millennia humans have used visible marks to communicate information. Modern examples of conventional graphical symbols include written language, and non-linguistic symbol systems such as mathematical symbology or traffic signs. The latter kinds of symbols convey information without reference to language. This book presents the first systematic study of graphical symbol systems, including a history of graphical symbols from the Paleolithic onwards, a taxonomy of non-linguistic systems - systems that are not tied to spoken language - and a survey of more than 25 such systems. One important feature of many non-linguistic systems is that, as in written language, symbols may be combined into complex "messages" if the information the system represents is itself complex. To illustrate, the author presents an in-depth comparison of two systems that had very similar functions, but very different structure: European heraldry and Japanese kamon. Writing first appeared in Mesopotamia about 5,000 years ago and is believed to have evolved from a previous non-linguistic accounting system. The exact mechanism is unknown, but crucial was the discovery that symbols can represent the sounds of words, not just the meanings. The book presents a novel neurologically-inspired hypothesis that writing evolved in an institutional context in which symbols were "dictated", thus driving an association between symbol and sound, and provides a computational simulation to support this hypothesis. The author further discusses some common fallacies about writing and non-linguistic systems, and how these relate to widely cited claims about statistical "evidence" for one or another system being writing. The book ends with some thoughts about the future of graphical symbol systems. The intended audience includes students, researchers, lecturers, professionals and scientists from fields like Natural Language Processing, Machine Learning, Archaeology and Semiotics, as well as general readers interested in language and/or writing systems and symbol systems. Richard Sproat is a Research Scientist at Google working on Deep Learning. He has a long-standing interest in writing systems and other graphical symbol systems.
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Computational linguistics.
9 (RLIN) 31390
Topical term or geographic name entry element Computational Linguistics.
9 (RLIN) 31391
Topical term or geographic name entry element Computer Application in Social and Behavioral Sciences.
9 (RLIN) 31392
Topical term or geographic name entry element Computer Modelling.
9 (RLIN) 31393
Topical term or geographic name entry element Computer simulation.
9 (RLIN) 31394
Topical term or geographic name entry element Digital humanities.
9 (RLIN) 31395
Topical term or geographic name entry element Digital Humanities.
9 (RLIN) 31396
Topical term or geographic name entry element Machine learning.
9 (RLIN) 31397
Topical term or geographic name entry element Machine Learning.
9 (RLIN) 31398
Topical term or geographic name entry element Natural language processing (Computer science).
9 (RLIN) 31399
Topical term or geographic name entry element Natural Language Processing (NLP).
9 (RLIN) 31400
Topical term or geographic name entry element Social sciences
9 (RLIN) 31401
856 ## - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier <a href="https://doi.org/10.1007/978-3-031-26809-0">https://doi.org/10.1007/978-3-031-26809-0</a>
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type e-Book
Source of classification or shelving scheme Dewey Decimal Classification
Holdings
Withdrawn status Lost status Damaged status Not for loan Home library Current library Shelving location Date acquired Source of acquisition Total Checkouts Barcode Date last seen Price effective from Koha item type Public note
        S. R. Ranganathan Learning Hub S. R. Ranganathan Learning Hub Online   Veda Library Solutions Pvt. Ltd., Noida   EB2196 2024-03-19 2024-03-19 e-Book Platform:Springer