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Data preparation: A technological perspective and review
Data analysis often uses data sets that were collected for different purposes. Indeed, new
insights are often obtained by combining data sets that were produced independently of …
insights are often obtained by combining data sets that were produced independently of …
Explaining dataset changes for semantic data versioning with explain-da-v
In multi-user environments in which data science and analysis is collaborative, multiple
versions of the same datasets are generated. While managing and storing data versions has …
versions of the same datasets are generated. While managing and storing data versions has …
A large reproducible benchmark on text classification for the legal domain based on the ECHR-OD repository
A Quemy, R Wrembel, N Łopuszyńska, G Papadakis… - Information Systems, 2023 - Elsevier
This work is a companion reproducible paper of our experiments and results reported in a
previous work Quemy and Wrembel (2022) introducing an open repository of legal …
previous work Quemy and Wrembel (2022) introducing an open repository of legal …
VADA: an architecture for end user informed data preparation
Background Data scientists spend considerable amounts of time preparing data for analysis.
Data preparation is labour intensive because the data scientist typically takes fine grained …
Data preparation is labour intensive because the data scientist typically takes fine grained …
Advances on data management and information systems
The research and technological area of data management encompasses various concepts,
techniques, algorithms and technologies, including data modeling, data integration and …
techniques, algorithms and technologies, including data modeling, data integration and …
An Evaluation Framework for Machine Learning and Data Science (ML/DS) Based Financial Strategies: A Case Study Driven Decision Model
Big data and computational technologies are increasingly important worldwide in asset and
investment management. Many investment management firms are adopting these data …
investment management. Many investment management firms are adopting these data …
A hierarchical decision model for evaluating the Strategy Readiness of Quantitative Machine Learning/Data science-driven investment strategies
M Saadatmand - 2024 - search.proquest.com
Big data and computational technologies are increasingly important worldwide in asset and
investment management. Many investment management firms are adopting these data …
investment management. Many investment management firms are adopting these data …
Boosting Methods Comparison: XGBoost, Adaboost and Gradient Boosting for Business Partner Performance Prediction
E Warni, DW Saputri, AAP Alimuddin… - 2024 8th …, 2024 - ieeexplore.ieee.org
Measuring the performance of business partners is a crucial technique for overseeing and
sustaining an organization or company's competitive edge. This process involves …
sustaining an organization or company's competitive edge. This process involves …
Explaining Dataset Changes for Semantic Data Versioning with Explain-Da-V (Technical Report)
In multi-user environments in which data science and analysis is collaborative, multiple
versions of the same datasets are generated. While managing and storing data versions has …
versions of the same datasets are generated. While managing and storing data versions has …
[PDF][PDF] SynthEdit: Format transformations by example using edit operations.
Format transformation is one of the most labor intensive tasks of a data wrangling process.
Recent advances in programming by example proposed synthesis algorithms that showed …
Recent advances in programming by example proposed synthesis algorithms that showed …