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008			230731s2023 sz | o |||| 0|eng d
020			_a9783031268090
024	7		_a10.1007/978-3-031-26809-0 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC _dES-MaUEC
050		4	_aQA76.9 .N38 _b2023 EB
100	1		_aSproat, Richard William _eautor _0(orcid)0000-0002-9040-5196 _1https://orcid.org/0000-0002-9040-5196 _4http://id.loc.gov/vocabulary/relators/aut _9687456
245	1	0	_aSymbols : _bAn Evolutionary History from the Stone Age to the Future _cby Richard Sproat
250			_a1st ed 2023
264		1	_aCham _bSpringer Nature Switzerland _c2023
300			_a1 recurso en línea
336			_atexto _btxt _2rdacontent
337			_aelectrónico _bc _2rdamedia
338			_arecurso electrónico _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.
988			_aSpringer_Computer_2023
650		7	_2embne _9158738 _aProceso en lenguaje natural (Informática)
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-031-26809-0 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE
998			_b02/2024 _dz _ek _zSI