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pro vyhledávání: '"Romero, Oscar"'
Spreadsheets are very successful content generation tools, used in almost every enterprise to create a wealth of information. However, this information is often intermingled with various formatting, layout, and textual metadata, making it hard to ide
Externí odkaz:
https://tud.qucosa.de/id/qucosa%3A82970
https://tud.qucosa.de/api/qucosa%3A82970/attachment/ATT-0/
https://tud.qucosa.de/api/qucosa%3A82970/attachment/ATT-0/
This paper presents DECO (Dresden Enron COrpus), a dataset of spreadsheet files, annotated on the basis of layout and contents. It comprises of 1,165 files, extracted from the Enron corpus. Three different annotators (judges) assigned layout roles (e
Externí odkaz:
https://tud.qucosa.de/id/qucosa%3A82977
https://tud.qucosa.de/api/qucosa%3A82977/attachment/ATT-0/
https://tud.qucosa.de/api/qucosa%3A82977/attachment/ATT-0/
Autor:
Fontenla-Romero, Oscar, Guijarro-Berdiñas, Bertha, Hernández-Pereira, Elena, Pérez-Sánchez, Beatriz
Nowadays, machine learning algorithms continue to grow in complexity and require a substantial amount of computational resources and energy. For these reasons, there is a growing awareness of the development of new green algorithms and distributed AI
Externí odkaz:
http://arxiv.org/abs/2312.14528
This paper presents a pipeline to detect and explain anomalous reviews in online platforms. The pipeline is made up of three modules and allows the detection of reviews that do not generate value for users due to either worthless or malicious composi
Externí odkaz:
http://arxiv.org/abs/2311.04948
Autor:
Munir, Rana Faisal, Nadal, Sergi, Romero, Oscar, Abelló, Alberto, Jovanovic, Petar, Thiele, Maik, Lehner, Wolfgang
Data-intensive flows deploy a variety of complex data transformations to build information pipelines from data sources to different end users. As data are processed, these workflows generate large intermediate results, typically pipelined from one op
Externí odkaz:
https://tud.qucosa.de/id/qucosa%3A72925
https://tud.qucosa.de/api/qucosa%3A72925/attachment/ATT-0/
https://tud.qucosa.de/api/qucosa%3A72925/attachment/ATT-0/
Spreadsheets compose a notably large and valuable dataset of documents within the enterprise settings and on the Web. Although spreadsheets are intuitive to use and equipped with powerful functionalities, extracting and reusing data from them remains
This paper explores the integration of two AI subdisciplines employed in the development of artificial agents that exhibit intelligent behavior: Large Language Models (LLMs) and Cognitive Architectures (CAs). We present three integration approaches,
Externí odkaz:
http://arxiv.org/abs/2308.09830
We study the problem of discovering joinable datasets at scale. We approach the problem from a learning perspective relying on profiles. These are succinct representations that capture the underlying characteristics of the schemata and data values of
Externí odkaz:
http://arxiv.org/abs/2305.19629
Publikováno v:
In Engineering Applications of Artificial Intelligence July 2024 133 Part B
Autor:
Mazón, Marina, Romero, Oscar
Publikováno v:
Caldasia, 2023 Jan 01. 45(1), 161-173.
Externí odkaz:
https://www.jstor.org/stable/48749412