TY  - JOUR
A1  - Jan-Micha, Bodensohn
A1  - Binnig, Carsten
T1  - Rethinking table retrieval from data lakes
T2  - Efl insights : an elf - the Data Science Institute publication
N2  - Existing table retrieval approaches estimate each table’s relevance for a particular information need and return a ranking of the most relevant tables. This approach is not ideal since the returned tables often include irrelevant data and the required information may be scattered across multiple tables. To address these issues, we propose the idea of fine-grained structured table retrieval and present our vision of R2D2, a system which slices tables into small tiles that are later composed into a structured result that is tailored to the user-provided information need. An initial evaluation of our approach demonstrates how our idea can improve table retrieval and relevant downstream tasks such as table question answering.
Y1  - 2024
UR  - http://publikationen.ub.uni-frankfurt.de/frontdoor/index/index/docId/80953
UR  - https://nbn-resolving.org/urn:nbn:de:hebis:30:3-809538
SN  - 1866-1238
SN  - 2700-2241
VL  - 2024
IS  - 2
SP  - 4
EP  - 5
PB  - E-Finance Lab e.V.
CY  - Frankfurt am Main
ER  -