Data Collection of Real-Life Knowledge Work in Context: The RLKWiC Dataset

Mahta Bakhshizadeh, Christian Jilek, Markus Schröder, Heiko Maus, Andreas Dengel
4/16/2024
cs.AI

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Abstract

Over the years, various approaches have been employed to enhance the productivity of knowledge workers, from addressing psychological well-being to the development of personal knowledge assistants. A significant challenge in this research area has been the absence of a comprehensive, publicly accessible dataset that mirrors real-world knowledge work. Although a handful of datasets exist, many are restricted in access or lack vital information dimensions, complicating meaningful comparison and benchmarking in the domain. This paper presents RLKWiC, a novel dataset of Real-Life Knowledge Work in Context, derived from monitoring the computer interactions of eight participants over a span of two months. As the first publicly available dataset offering a wealth of essential information dimensions (such as explicated contexts, textual contents, and semantics), RLKWiC seeks to address the research gap in the personal information management domain, providing valuable insights for modeling user behavior.

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@article{bakhshizadeh2024data,
  title  = {Data Collection of Real-Life Knowledge Work in Context: The RLKWiC Dataset},
  author = {Mahta Bakhshizadeh and Christian Jilek and Markus Schröder and Heiko Maus and Andreas Dengel},
  year   = {2024},
  eprint = {2404.10505},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2404.10505v1}
}

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