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1
Reviewed by:
In: http://journal.frontiersin.org/Journal/10.3389/fpsyg.2014.00407/pdf/ (2014)
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2
Developing semantic knowledge through cross-situational word learning
In: http://www.kachergis.com/docs/kachergis_yu_shiffrin_2014_priming.pdf (2014)
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3
Exploring the Relationship of Motivation, Anxiety, and Virtual Worlds in the! Experiences of Two Spanish Language Learners: A Case Study!!!
In: http://scholarcommons.usf.edu/cgi/viewcontent.cgi?article%3D6347%26context%3Detd (2014)
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4
Reviewed by:
In: http://www.kachergis.com/docs/kachergis_yu_shiffrin_2014frontiers_implicit.pdf (2014)
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5
Markers of Topical Discourse in Child-Directed Speech
In: http://langcog.stanford.edu/papers/RF-cogsci2014.pdf (2013)
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6
Learning phonemes with a proto-lexicon
In: http://www.lscp.net/persons/dupoux/papers/Martin_PD_2012_learning_phonemes_with_pseudolexicon.pdf (2013)
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7
Learning phonemes with a protolexicon
In: http://www.lscp.net/persons/peperkamp/Martin_Peperkamp_Dupoux_(2013)_Learning_phonemes_with_a_proto-lexicon.pdf (2013)
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8
Language Learning From Positive Evidence, Reconsidered: A Simplicity-Based Approach
In: http://homepages.cwi.nl/~paulv/papers/tcs13.pdf (2013)
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9
Actively learning object names across ambiguous situations
In: http://www.kachergis.com/docs/kachergis_etal2013_active.pdf (2013)
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10
Edited by:
In: http://oro.open.ac.uk/37584/1/fpsyg-04-00255.pdf (2013)
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11
Author manuscript, published in "CSLP, France (2012)" On Language Acquisition Through Womb Grammars
In: http://hal.inria.fr/docs/00/75/18/50/PDF/dmb_CSLP12.pdf (2012)
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12
Learning Nouns with Domain-General Associative Learning Mechanisms
In: http://www.kachergis.com/docs/Kachergis_2012CogSci_paper616_domain-general.pdf (2012)
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13
R.: WiSeNet: Building a Wikipedia-based semantic network with ontologized relations
In: http://wwwusers.di.uniroma1.it/~navigli/pubs/CIKM_2012_Moro_Navigli.pdf (2012)
Abstract: In this paper we present an approach for building a Wikipedia-based semantic network by integrating Open Information Extraction with Knowledge Acquisition techniques. Our algorithm extracts relation instances from Wikipedia page bodies and ontologizes them by, first, creating sets of synonymous relational phrases, called relation synsets, second, assigning semantic classes to the arguments of these relation synsets and, third, disambiguating the initial relation instances with relation synsets. As a result we obtain WiSeNet, a Wikipedia-based Semantic Network with Wikipedia pages as concepts and labeled, ontologized relations between them.
Keyword: Categories and Subject Descriptors I.2.4 [Artificial Intelligence; Experimentation Keywords Information Extraction; I.2.6 [Artificial Intelligence; I.2.7 [Artificial Intelligence; Knowledge Acquisition; Knowledge Representation Formalisms and Methods – Semantic networks; Learning – Knowledge acquisition; Natural Language Processing General Terms Algorithms; Relation Ontologization; Semantic Network
URL: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.308.3678
http://wwwusers.di.uniroma1.it/~navigli/pubs/CIKM_2012_Moro_Navigli.pdf
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14
Relating activity contexts to early word learning in dense longitudinal data
In: http://www.media.mit.edu/cogmac/publications/cogsci2012_RFR_fix.pdf (2012)
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15
Relating activity contexts to early word learning in dense longitudinal data
In: http://web.media.mit.edu/~dkroy/papers/pdf/cogsci2012_RFR.pdf (2012)
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16
Impact of Parents ‘ Profession on their Children‘s Learning
In: http://www.macrothink.org/journal/index.php/ijld/article/download/1384/1132/ (2012)
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17
Reviewed by:
In: http://brainvitge.org/papers/Arciuli_KossTorkidsen_FrontinPsycho_2012.pdf (2012)
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18
Does Statistical Word Learning Scale? It’s a Matter of Perspective
In: http://www.thoughtfill.com/docs/yurovsky_smith_yu_cs12.pdf (2012)
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19
Actively Learning Object Names Across Ambiguous Situations
In: http://www.indiana.edu/~dll/papers/kachergis2012_active_topics.pdf (2012)
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20
Reviewed by:
In: ftp://ftp.ncbi.nlm.nih.gov/pub/pmc/df/ed/Front_Psychol_2012_Mar_28_3_88.tar.gz (2012)
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