TY  - CHAP
U1  - Konferenzveröffentlichung
A1  - Fankhauser, Peter
A1  - Kupietz, Marc
ED  - Bański, Piotr
ED  - Barbaresi, Adrien
ED  - Clematide, Simon
ED  - Kupietz, Marc
ED  - Lüngen, Harald
T1  - Count-based and predictive language models for exploring DeReKo
T2  - Proceedings of the LREC 2022 Workshop on Challenges in the Management of Large Corpora (CMLC-10 2022). Marseille, 20 June 2022
N2  - We present the use of count-based and predictive language models for exploring language use in the German Reference Corpus DeReKo. For collocation analysis along the syntagmatic axis we employ traditional association measures based on co-occurrence counts as well as predictive association measures derived from the output weights of skipgram word embeddings. For inspecting the semantic neighbourhood of words along the paradigmatic axis we visualize the high dimensional word embeddings in two dimensions using t-stochastic neighbourhood embeddings. Together, these visualizations provide a complementary, explorative approach to analysing very large corpora in addition to corpus querying. Moreover, we discuss count-based and predictive models w.r.t. scalability and maintainability in very large corpora.
KW  - language models
KW  - word embeddings
KW  - collocation analysis
KW  - Korpus <Linguistik>
KW  - Deutsch
KW  - Kollokation
KW  - Syntagma
KW  - Assoziationsmaß
KW  - Paradigma
KW  - German Reference Corpus (DeReKo)
KW  - Deutsches Referenzkorpus (DeReKo)
Y1  - 2022
U6  - https://nbn-resolving.org/urn:nbn:de:bsz:mh39-111107
UN  - https://nbn-resolving.org/urn:nbn:de:bsz:mh39-111107
UR  - http://www.lrec-conf.org/proceedings/lrec2022/workshops/CMLC10/pdf/2022.cmlc10-1.5.pdf
SN  - 979-10-95546-83-2
SB  - 979-10-95546-83-2
SP  - 27
EP  - 31
PB  - European Language Resources Association (ELRA)
CY  - Paris
ER  -