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340373 VO Multilingual and Crosslingual Methods and Language Resources (2022W)
Labels
Registration/Deregistration
Note: The time of your registration within the registration period has no effect on the allocation of places (no first come, first served).
Details
max. 1000 participants
Language: English
Examination dates
- Wednesday 25.01.2023 18:30 - 20:00 Hörsaal 3A ZfT Gymnasiumstraße 50 3.OG
- Wednesday 01.03.2023 18:30 - 20:00 Seminarraum 9 ZfT Philippovichgasse 11, 2.OG
- Wednesday 26.04.2023 18:30 - 20:00 Hörsaal 4 ZfT Gymnasiumstraße 50 3.OG
- Wednesday 28.06.2023 18:30 - 20:00 Hörsaal 3A ZfT Gymnasiumstraße 50 3.OG
Lecturers
Classes (iCal) - next class is marked with N
This lecture will be held in English every Wednesday from 12.10.2022 to 25.01.2023 from 6.30 to 8 pm in lecture hall 3A, ZfT Gymnasiumstraße 50, 3. floor.
- Wednesday 12.10. 18:30 - 20:00 Hörsaal 3A ZfT Gymnasiumstraße 50 3.OG
- Wednesday 19.10. 18:30 - 20:00 Hörsaal 3A ZfT Gymnasiumstraße 50 3.OG
- Wednesday 09.11. 18:30 - 20:00 Hörsaal 3A ZfT Gymnasiumstraße 50 3.OG
- Wednesday 16.11. 18:30 - 20:00 Hörsaal 3A ZfT Gymnasiumstraße 50 3.OG
- Wednesday 30.11. 18:30 - 20:00 Hörsaal 3A ZfT Gymnasiumstraße 50 3.OG
- Wednesday 07.12. 18:30 - 20:00 Hörsaal 3A ZfT Gymnasiumstraße 50 3.OG
- Wednesday 14.12. 18:30 - 20:00 Hörsaal 3A ZfT Gymnasiumstraße 50 3.OG
- Wednesday 11.01. 18:30 - 20:00 Hörsaal 3A ZfT Gymnasiumstraße 50 3.OG
- Wednesday 18.01. 18:30 - 20:00 Hörsaal 3A ZfT Gymnasiumstraße 50 3.OG
Information
Aims, contents and method of the course
Assessment and permitted materials
Written exam and bonus points.Bonus points: During the semester additional exercises to the contents of this lecture will be provided on Moodle, which will be announced and described in the respective digital lectures. Completing these exercises will grant you bonus points that count towards the final written exam.Can I pass the lecture solely based on bonus points?
No, bonus points alone are insufficient to obtain a positive final evaluation of the lecture. However, a negative result on the written exam that was almost a pass might be turned positive due to bonus points.Do I require bonus points to obtain the total number of points on the written exam?
No, the total number of points on the final written exam can be obtained without bonus points. There will be no disadvantage for you if you do not have any bonus points. However, if you do obtain bonus points, your grade can improve by up to maximum one grade (e.g. if you obtain a good 3, the bonus points might boost your grade to a 2).How can I keep track of my bonus points?
Your bonus points will be documented on the Moodle page of the lecture.How long are the obtained bonus points valid?
The bonus points are at maximum valid until the end of the semester following the semester of the lecture (e.g. lecture 2022W - bonus points are valid for all 4 exams of the following semester).
No, bonus points alone are insufficient to obtain a positive final evaluation of the lecture. However, a negative result on the written exam that was almost a pass might be turned positive due to bonus points.Do I require bonus points to obtain the total number of points on the written exam?
No, the total number of points on the final written exam can be obtained without bonus points. There will be no disadvantage for you if you do not have any bonus points. However, if you do obtain bonus points, your grade can improve by up to maximum one grade (e.g. if you obtain a good 3, the bonus points might boost your grade to a 2).How can I keep track of my bonus points?
Your bonus points will be documented on the Moodle page of the lecture.How long are the obtained bonus points valid?
The bonus points are at maximum valid until the end of the semester following the semester of the lecture (e.g. lecture 2022W - bonus points are valid for all 4 exams of the following semester).
Minimum requirements and assessment criteria
Minimum requirement: positive performance on the written examGrading:
0-60% 5 (fail),
61-70% 4,
71-80% 3,
81-90% 2,
91-100% 1
0-60% 5 (fail),
61-70% 4,
71-80% 3,
81-90% 2,
91-100% 1
Examination topics
All contents discussed in the lecture and course literature (see Moodle).
Reading list
Will be announced in the first class of the lecture and on Moodle.Examples of literature:
Ammar, W., Mulcaire, G., Tsvetkov, Y., Lample, G., Dyer, C., & Smith, N. A. (2016). Massively multilingual word embeddings. arXiv preprint arXiv:1602.01925.Bosque-Gil, J., Gracia, J., Montiel-Ponsoda, E., & Gómez-Pérez, A. (2018). Models to represent linguistic linked data. Natural Language Engineering, 24(6), 811-859.Chiarcos, C., McCrae, J., Cimiano, P., & Fellbaum, C. (2013). Towards open data for linguistics: Linguistic linked data. In New Trends of Research in Ontologies and Lexical Resources (pp. 7-25). Springer, Berlin, Heidelberg.Cimiano, P., Chiarcos, C., McCrae, J. P., & Gracia, J. (2020). Linguistic Linked Data in Digital Humanities. In Linguistic Linked Data (pp. 229-262). Springer, Cham.Forkel, R. (2014). The cross-linguistic linked data project. In 3rd Workshop on Linked Data in Linguistics: Multilingual Knowledge Resources and Natural Language Processing (p. 61).McCrae, J. P., Moran, S., Hellmann, S., & Brümmer, M. (2015). Multilingual linked data. Semantic Web, 6(4), 315-317.McCrae, J. P., Bosque-Gil, J., Gracia, J., Buitelaar, P., & Cimiano, P. (2017). The Ontolex-Lemon model: development and applications. In Proceedings of eLex 2017 conference (pp. 19-21).Ruder, S., Vulić, I., & Søgaard, A. (2019). A survey of cross-lingual word embedding models. Journal of Artificial Intelligence Research, 65, 569-631.
Ammar, W., Mulcaire, G., Tsvetkov, Y., Lample, G., Dyer, C., & Smith, N. A. (2016). Massively multilingual word embeddings. arXiv preprint arXiv:1602.01925.Bosque-Gil, J., Gracia, J., Montiel-Ponsoda, E., & Gómez-Pérez, A. (2018). Models to represent linguistic linked data. Natural Language Engineering, 24(6), 811-859.Chiarcos, C., McCrae, J., Cimiano, P., & Fellbaum, C. (2013). Towards open data for linguistics: Linguistic linked data. In New Trends of Research in Ontologies and Lexical Resources (pp. 7-25). Springer, Berlin, Heidelberg.Cimiano, P., Chiarcos, C., McCrae, J. P., & Gracia, J. (2020). Linguistic Linked Data in Digital Humanities. In Linguistic Linked Data (pp. 229-262). Springer, Cham.Forkel, R. (2014). The cross-linguistic linked data project. In 3rd Workshop on Linked Data in Linguistics: Multilingual Knowledge Resources and Natural Language Processing (p. 61).McCrae, J. P., Moran, S., Hellmann, S., & Brümmer, M. (2015). Multilingual linked data. Semantic Web, 6(4), 315-317.McCrae, J. P., Bosque-Gil, J., Gracia, J., Buitelaar, P., & Cimiano, P. (2017). The Ontolex-Lemon model: development and applications. In Proceedings of eLex 2017 conference (pp. 19-21).Ruder, S., Vulić, I., & Søgaard, A. (2019). A survey of cross-lingual word embedding models. Journal of Artificial Intelligence Research, 65, 569-631.
Association in the course directory
Last modified: Th 06.07.2023 17:08
- different types of language resources (terminology, lexica, controlled vocabularies, thesaurus, etc.)
- methods for the representation, generation, processing and usage of multilingual language resources, including Linguistic Linked Open Data (LLOD) and linguistic data science in general
- multilingual and cross-lingual methods to assist communication with language resources and computational linguistic approaches
- practical examples for the above methodsMethod:
- theoretical introduction to different language resources
- theoretical introduction to different multilingual and cross-lingual methods for language technologies, e.g. word embeddings and LLOD
- theoretical discussion of the current state of the art
- practical case studies for multilingual and cross-lingual resources and methods