Zobrazeno 1 - 4
of 4
pro vyhledávání: '"Christoph Kilian Theil"'
Publikováno v:
ACM/IMS Transactions on Data Science. 1:1-19
The detection of vague, speculative, or otherwise uncertain language has been performed in the encyclopedic, political, and scientific domains yet left relatively untouched in finance. However, the latter benefits from public sources of big financial
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7ce732e26d7aa1c44807dd5302b1d25f
https://doi.org/10.1145/3343039
https://doi.org/10.1145/3343039
Publikováno v:
IJCAI
MADOC-University of Mannheim
MADOC-University of Mannheim
Financial risk, defined as the chance to deviate from return expectations, is most commonly measured with volatility. Due to its value for investment decision making, volatility prediction is probably among the most important tasks in finance and ris
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::11ab7817b74275d54a570330347bce0f
https://doi.org/10.24963/ijcai.2019/724
https://doi.org/10.24963/ijcai.2019/724
Publikováno v:
Computational Linguistics and Intelligent Text Processing ISBN: 9783319771151
CICLing (2)
CICLing (2)
The automatic detection of uncertain statements can benefit NLP tasks such as deception detection and information extraction. Furthermore, it can enable new analyses in social sciences such as business where the quantification of uncertainty or risk
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ad15fec83eccd51d5c3654f2081a88a7
https://doi.org/10.1007/978-3-319-77116-8_48
https://doi.org/10.1007/978-3-319-77116-8_48
Publikováno v:
ECONLP@ACL
MADOC-University of Mannheim
MADOC-University of Mannheim
In this paper, we use NLP techniques to detect linguistic uncertainty in financial disclosures. Leveraging general-domain and domain-specific word embedding models, we automatically expand an existing dictionary of uncertainty triggers. We furthermor
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::22914e18e6968d32a37d62813963e400
https://doi.org/10.18653/v1/w18-3104
https://doi.org/10.18653/v1/w18-3104