Knowledge Modelling and Learning through Cognitive Networks
One of the most promising developments in modelling knowledge is cognitive network science, which aims to investigate cognitive phenomena driven by the networked, associative organization of knowledge. For example, investigating the structure of semantic memory via semantic networks has illuminated...
Gorde:
| Formatua: | Online |
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| Hizkuntza: | ingelesa |
| Argitaratua: |
MDPI - Multidisciplinary Digital Publishing Institute
2022
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| Gaiak: | |
| Sarrera elektronikoa: | ONIX_20220706_9783036543451_57 |
| Etiketak: |
Etiketarik gabe, Izan zaitez lehena erregistro honi etiketa jartzen!
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| _version_ | 1869514641471700992 |
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| collection | Directory of Open Access Books |
| description | One of the most promising developments in modelling knowledge is cognitive network science, which aims to investigate cognitive phenomena driven by the networked, associative organization of knowledge. For example, investigating the structure of semantic memory via semantic networks has illuminated how memory recall patterns influence phenomena such as creativity, memory search, learning, and more generally, knowledge acquisition, exploration, and exploitation. In parallel, neural network models for artificial intelligence (AI) are also becoming more widespread as inferential models for understanding which features drive language-related phenomena such as meaning reconstruction, stance detection, and emotional profiling. Whereas cognitive networks map explicitly which entities engage in associative relationships, neural networks perform an implicit mapping of correlations in cognitive data as weights, obtained after training over labelled data and whose interpretation is not immediately evident to the experimenter. This book aims to bring together quantitative, innovative research that focuses on modelling knowledge through cognitive and neural networks to gain insight into mechanisms driving cognitive processes related to knowledge structuring, exploration, and learning. The book comprises a variety of publication types, including reviews and theoretical papers, empirical research, computational modelling, and big data analysis. All papers here share a commonality: they demonstrate how the application of network science and AI can extend and broaden cognitive science in ways that traditional approaches cannot. |
| format | Online |
| id | doab-20.500.12854ir-87462 |
| institution | Directory of Open Access Books |
| language | eng |
| publishDate | 2022 |
| publishDateRange | 2022 |
| publishDateSort | 2022 |
| publisher | MDPI - Multidisciplinary Digital Publishing Institute |
| publisherStr | MDPI - Multidisciplinary Digital Publishing Institute |
| record_format | ojs |
| spelling | doab-20.500.12854ir-874622024-03-30T12:51:00Z Knowledge Modelling and Learning through Cognitive Networks Stella, Massimo Kenett, Yoed N. text mining big data analytics review self-organization computational philosophy brain synaptic learning adaptation functional plasticity activity-dependent resonance states circular causality somatosensory representation prehensile synergies robotics COVID-19 social media hashtag networks emotional profiling cognitive science network science sentiment analysis computational social science Twitter VADER scoring correlation semantic network analysis intellectual disability adolescents EEG emotional states working memory depression anxiety graph theory classification machine learning neural networks phonotactic probability neighborhood density sub-lexical representations lexical representations phonemes biphones cognitive network smart assistants knowledge generation intelligent systems web components deep learning web-based interaction cognitive network science text analysis natural language processing artificial intelligence emotional recall cognitive data AI pharmacological text corpus automatic relation extraction gender stereotypes story tropes movie plots network analysis word co-occurrence network n/a thema EDItEUR::K Economics, Finance, Business and Management::KN Industry and industrial studies::KNT Media, entertainment, information and communication industries::KNTX Information technology industries One of the most promising developments in modelling knowledge is cognitive network science, which aims to investigate cognitive phenomena driven by the networked, associative organization of knowledge. For example, investigating the structure of semantic memory via semantic networks has illuminated how memory recall patterns influence phenomena such as creativity, memory search, learning, and more generally, knowledge acquisition, exploration, and exploitation. In parallel, neural network models for artificial intelligence (AI) are also becoming more widespread as inferential models for understanding which features drive language-related phenomena such as meaning reconstruction, stance detection, and emotional profiling. Whereas cognitive networks map explicitly which entities engage in associative relationships, neural networks perform an implicit mapping of correlations in cognitive data as weights, obtained after training over labelled data and whose interpretation is not immediately evident to the experimenter. This book aims to bring together quantitative, innovative research that focuses on modelling knowledge through cognitive and neural networks to gain insight into mechanisms driving cognitive processes related to knowledge structuring, exploration, and learning. The book comprises a variety of publication types, including reviews and theoretical papers, empirical research, computational modelling, and big data analysis. All papers here share a commonality: they demonstrate how the application of network science and AI can extend and broaden cognitive science in ways that traditional approaches cannot. 2022-07-06T11:50:53Z 2022-07-06T11:50:53Z 2022 book ONIX_20220706_9783036543451_57 9783036543451 9783036543468 https://directory.doabooks.org/handle/20.500.12854/87462 eng application/octet-stream Attribution 4.0 International https://mdpi.com/books/pdfview/book/5650 https://mdpi.com/books/pdfview/book/5650 MDPI - Multidisciplinary Digital Publishing Institute 10.3390/books978-3-0365-4346-8 10.3390/books978-3-0365-4346-8 46cabcaa-dd94-4bfe-87b4-55023c1b36d0 9783036543451 9783036543468 240 Basel open access |
| spellingShingle | text mining big data analytics review self-organization computational philosophy brain synaptic learning adaptation functional plasticity activity-dependent resonance states circular causality somatosensory representation prehensile synergies robotics COVID-19 social media hashtag networks emotional profiling cognitive science network science sentiment analysis computational social science VADER scoring correlation semantic network analysis intellectual disability adolescents EEG emotional states working memory depression anxiety graph theory classification machine learning neural networks phonotactic probability neighborhood density sub-lexical representations lexical representations phonemes biphones cognitive network smart assistants knowledge generation intelligent systems web components deep learning web-based interaction cognitive network science text analysis natural language processing artificial intelligence emotional recall cognitive data AI pharmacological text corpus automatic relation extraction gender stereotypes story tropes movie plots network analysis word co-occurrence network n/a thema EDItEUR::K Economics, Finance, Business and Management::KN Industry and industrial studies::KNT Media, entertainment, information and communication industries::KNTX Information technology industries Knowledge Modelling and Learning through Cognitive Networks |
| title | Knowledge Modelling and Learning through Cognitive Networks |
| title_full | Knowledge Modelling and Learning through Cognitive Networks |
| title_fullStr | Knowledge Modelling and Learning through Cognitive Networks |
| title_full_unstemmed | Knowledge Modelling and Learning through Cognitive Networks |
| title_short | Knowledge Modelling and Learning through Cognitive Networks |
| title_sort | knowledge modelling and learning through cognitive networks |
| topic | text mining big data analytics review self-organization computational philosophy brain synaptic learning adaptation functional plasticity activity-dependent resonance states circular causality somatosensory representation prehensile synergies robotics COVID-19 social media hashtag networks emotional profiling cognitive science network science sentiment analysis computational social science VADER scoring correlation semantic network analysis intellectual disability adolescents EEG emotional states working memory depression anxiety graph theory classification machine learning neural networks phonotactic probability neighborhood density sub-lexical representations lexical representations phonemes biphones cognitive network smart assistants knowledge generation intelligent systems web components deep learning web-based interaction cognitive network science text analysis natural language processing artificial intelligence emotional recall cognitive data AI pharmacological text corpus automatic relation extraction gender stereotypes story tropes movie plots network analysis word co-occurrence network n/a thema EDItEUR::K Economics, Finance, Business and Management::KN Industry and industrial studies::KNT Media, entertainment, information and communication industries::KNTX Information technology industries |
| topic_facet | text mining big data analytics review self-organization computational philosophy brain synaptic learning adaptation functional plasticity activity-dependent resonance states circular causality somatosensory representation prehensile synergies robotics COVID-19 social media hashtag networks emotional profiling cognitive science network science sentiment analysis computational social science VADER scoring correlation semantic network analysis intellectual disability adolescents EEG emotional states working memory depression anxiety graph theory classification machine learning neural networks phonotactic probability neighborhood density sub-lexical representations lexical representations phonemes biphones cognitive network smart assistants knowledge generation intelligent systems web components deep learning web-based interaction cognitive network science text analysis natural language processing artificial intelligence emotional recall cognitive data AI pharmacological text corpus automatic relation extraction gender stereotypes story tropes movie plots network analysis word co-occurrence network n/a thema EDItEUR::K Economics, Finance, Business and Management::KN Industry and industrial studies::KNT Media, entertainment, information and communication industries::KNTX Information technology industries |
| url | ONIX_20220706_9783036543451_57 |