000 04530nam a22005895i 4500
001 978-3-031-26809-0
003 DE-He213
005 20240423125439.0
007 cr nn 008mamaa
008 230731s2023 sz | s |||| 0|eng d
020 _a9783031268090
_9978-3-031-26809-0
024 7 _a10.1007/978-3-031-26809-0
_2doi
050 4 _aQA76.9.N38
072 7 _aUYQL
_2bicssc
072 7 _aCOM073000
_2bisacsh
072 7 _aUYQL
_2thema
082 0 4 _a006.35
_223
100 1 _aSproat, Richard.
_eauthor.
_0(orcid)
_10000-0002-9040-5196
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
245 1 0 _aSymbols
_h[electronic resource] :
_bAn Evolutionary History from the Stone Age to the Future /
_cby Richard Sproat.
250 _a1st ed. 2023.
264 1 _aCham :
_bSpringer Nature Switzerland :
_bImprint: Springer,
_c2023.
300 _aXIII, 235 p. 91 illus., 57 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
505 0 _a1. Introduction -- 2. Semiotics -- 3. Taxonomy -- 4. Writing Systems -- 5. Symbols in the Brain -- 6. The Evolution of Writing -- 7. Simulations -- 8. Misrepresentations -- 9. The Future.
520 _aFor 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 0 _aNatural language processing (Computer science).
650 0 _aMachine learning.
650 0 _aDigital humanities.
650 0 _aSocial sciences
_xData processing.
650 0 _aComputational linguistics.
650 0 _aComputer simulation.
650 1 4 _aNatural Language Processing (NLP).
650 2 4 _aMachine Learning.
650 2 4 _aDigital Humanities.
650 2 4 _aComputer Application in Social and Behavioral Sciences.
650 2 4 _aComputational Linguistics.
650 2 4 _aComputer Modelling.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783031268083
776 0 8 _iPrinted edition:
_z9783031268106
776 0 8 _iPrinted edition:
_z9783031268113
856 4 0 _uhttps://doi.org/10.1007/978-3-031-26809-0
912 _aZDB-2-SCS
912 _aZDB-2-SXCS
942 _cSPRINGER
999 _c178042
_d178042