EDBT 2026 Demo / reviewers in the wild / expert
Blanca Carbajo-Coronado
dblp:367/1645
· DBLP profile ↗
2ranked-venue papers in the field
0as first author
2since 2021 · last 2023
0000-0001-7693-0042ORCID · verified
Domains — venue-derived; a paper can count in several
Big Data, Cloud & Distributed Data Systems · 2
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2023 | The Financial Document Causality Detection Shared Task (FinCausal 2023)abstractWe introduce the FinCausal 2023 Shared Task on Causality Detection in Financial Documents and the corresponding FinCausal dataset. This paper also provides insights into the participating systems and their outcomes. The primary objective of this task is to identify whether an object, event or sequence of events can be considered the cause of a preceding event (the effect). This year, we presented two subtasks, one in English and another in Spanish. In both subtasks, participants were tasked with pinpointing, within causal sentences, the elements that pertained to the cause and those that related to the effect. We received system runs from five teams for the English subtask and three teams for the Spanish subtask. FinCausal 2023 is affiliated with the 5th Financial Narrative Processing Workshop (FNP 2023), hosted at IEEE BigData 2023 in Sorrento, Italy. Antonio Moreno-Sandoval, Jordi Porta-Zamorano, Blanca Carbajo-Coronado, Doaa Samy, Dominique Mariko, Mahmoud El-Haj |
IEEE Big Data | 3 |
| 2023 | The Financial Narrative Summarisation Shared Task (FNS 2023)abstractThis paper presents the results and findings of the Financial Narrative Summarisation Shared Task on summarising UK, Greek, and Spanish annual reports. The shared task was organised as part of the 5th Financial Narrative Processing Workshop (FNP 2023). The Financial Narrative summarisation Shared Task (FNS 2023) has been running since 2020 as part of the Financial Narrative Processing (FNP) workshop series [15–20]. The shared task included one main challenge, which is the use of either abstractive or extractive automatic summarisers to summarise long documents in terms of UK, Greek, and Spanish financial annual reports. This shared task is the fourth to target financial documents. The data for the shared task was created and collected from publicly available annual reports published by firms listed on the Stock Exchanges of the UK, Greece, and Spain. A total number of 6 systems from 3 different teams participated in the shared task. Elias Zavitsanos, Aris Kosmopoulos, George Giannakopoulos, Marina Litvak, Blanca Carbajo-Coronado, Antonio Moreno-Sandoval, Mo El-Haj |
IEEE Big Data | 5 |