Encyclopedia of Database Systems

Living Edition
| Editors: Ling Liu, M. Tamer Özsu

Crowd Mining and Analysis

  • Yael Amsterdamer
  • Tova Milo
Living reference work entry
DOI: https://doi.org/10.1007/978-1-4899-7993-3_80657-2


Crowd mining is the process of identifying data patterns in human knowledge, with the assistance of a crowd of web users. The focus is on domain areas in which data is partially or entirely undocumented and where humans are the main source of knowledge, such as data that involves people’s habits, experiences, and opinions. A key challenge in mining such data is that the human knowledge forms an open world and it is thus difficult to know what kind of information one should be looking for.

In classic databases, a similar problem is addressed by data mining techniques that identify interesting patterns in recorded data such as relational databases or textual documents. These techniques, however, are not suitable for the crowd. This is mainly due to properties of the human memory, such as the tendency to remember simple trends and summaries rather than exact details, which should be taken into consideration when gathering and analyzing...


Data Item Data Pattern Tomato Sauce Food Dish Natural Language Interface 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Copyright information

© Springer Science+Business Media LLC 2017

Authors and Affiliations

  1. 1.Department of Computer ScienceBar Ilan UniversityRamat GanIsrael
  2. 2.School of Computer ScienceTel Aviv UniversityTel AvivIsrael

Section editors and affiliations

  • Reynold Cheng
    • 1
  1. 1.Computer ScienceThe University of Hong KongHong KongChina