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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Hits 1 – 5 of 5 1 A Text Structure Indicator and two Topological Methods: New Ways for Studying Latin Historic Narratives Longrée, Dominique; Mellet, Sylvie In: ISSN: 2055-7671 ; EISSN: 2055-768X ; Digital Scholarship in the Humanities ; https://hal.archives-ouvertes.fr/hal-01337493 ; Digital Scholarship in the Humanities, Oxford University Press, 2016, ⟨10.1093/llc/fqw021⟩ ; http://dsh.oxfordjournals.org/cgi/content/full/fqw021? ijkey=wDyZkoG1iV8aqRa&keytype=ref (2016) BASE Show details 2 Les anaphores rhétoriques : des rafales de motifs ? Longrée, Dominique; Mayaffre, Damon; Mellet, Sylvie In: Jadt 2016 - Statistical Analysis of Textual Data ; https://hal.archives-ouvertes.fr/hal-01361991 ; JADT 2016 - Statistical Analysis of Textual Data, Damon Mayaffre; Céline Poudat; Laurent Vanni; Véronique Magri; Peter Follette; Caroline Daire, Jun 2016, Nice, France. pp.319-328 (2016) BASE Show details 3 The contribution of the research on Latin texts to the French quantitative linguistics : from lemmatization to the grammaticometry and textual topology Longrée, Dominique; Mellet, Sylvie In: Quantitative Linguistics in France ; https://hal.univ-cotedazur.fr/hal-01364998 ; Jacqueline Leon, Sylvain Loiseau (eds.). Quantitative Linguistics in France, RAM Verlag, sous presse, 2016 (2016) BASE Show details 4 Semantic integration by pattern priming: experiment and cortical network model Lavigne, Frédéric; Longrée, Dominique; Mayaffre, Damon; Mellet, Sylvie In: ISSN: 1871-4080 ; EISSN: 1871-4099 ; Cognitive Neurodynamics ; https://hal.archives-ouvertes.fr/hal-01365139 ; Cognitive Neurodynamics, Springer Verlag, 2016, ⟨10.1007/s11571-016-9410-4⟩ (2016) Abstract: International audience ; Neural network models describe semantic priming effects by way of mechanisms of activation of neuron coding for the words that rely strongly on synaptic efficacies between pairs of neurons. Biologically inspired Hebbian learning defines efficacy values as a function of the activity of pre- and post-synaptic neurons only. It generates only pair associations between words in the semantic network. However, the statistical analysis of large text databases points to the frequent occurrence not only of pairs of words (e.g., “the way”) but also of patterns of more than two words (e.g., “by the way”). The learning of these frequent patterns of words is not reducible to associations between pairs of words but must take into account the higher level of coding of three-word patterns. The processing and learning of pattern of words challenges classical Hebbian learning algorithms used in biologically inspired models of priming. The aim of the present study was to test the effects of patterns on the semantic processing of words and investigates how an inter-synaptic learning algorithm succeeds at reproducing the experimental data.The experiment manipulates the frequency of occurrence of patterns of three words in a multiple-paradigm protocol. Results show for the first time that target words benefit more priming when embedded in a pattern with the two primes than when only associated with each prime in a pair. A biologically inspired, inter-synaptic learning algorithm is tested that potentiates synapses as a function of the activation of more than two pre- and post-synaptic neurons. Simulations show that the network can learn patterns of three words to reproduce the experimental results Keyword: [SCCO.NEUR]Cognitive science/Neuroscience; [SCCO.PSYC]Cognitive science/Psychology; [SHS.LANGUE]Humanities and Social Sciences/Linguistics; Context; inter-synaptic learning; multiple priming; prospective activity; word meaning; word occurrence URL: https://hal.archives-ouvertes.fr/hal-01365139 https://doi.org/10.1007/s11571-016-9410-4 BASE Hide details 5 Semantic integration by pattern priming: experiment and cortical network model Lavigne, Frédéric; Longrée, Dominique; Mayaffre, Damon. - : Springer Netherlands, 2016 BASE Show details

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