6533b870fe1ef96bd12cf3bb
RESEARCH PRODUCT
HUMAN: Hierarchical Universal Modular ANnotator
Moritz WolfDana RuiterDietrich KlakowJan AlexanderssonAshwin Geet D'saLiane Reinerssubject
FOS: Computer and information sciences0303 health sciencesComputer Science - Computation and Languagebusiness.industryActive learning (machine learning)Computer science02 engineering and technology[INFO] Computer Science [cs]Modular designVariety (cybernetics)Task (project management)03 medical and health sciencesAnnotationHuman–computer interaction0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processing[INFO]Computer Science [cs]businessComputation and Language (cs.CL)030304 developmental biologyGraphical user interfacedescription
A lot of real-world phenomena are complex and cannot be captured by single task annotations. This causes a need for subsequent annotations, with interdependent questions and answers describing the nature of the subject at hand. Even in the case a phenomenon is easily captured by a single task, the high specialisation of most annotation tools can result in having to switch to another tool if the task only slightly changes. We introduce HUMAN, a novel web-based annotation tool that addresses the above problems by a) covering a variety of annotation tasks on both textual and image data, and b) the usage of an internal deterministic state machine, allowing the researcher to chain different annotation tasks in an interdependent manner. Further, the modular nature of the tool makes it easy to define new annotation tasks and integrate machine learning algorithms e.g., for active learning. HUMAN comes with an easy-to-use graphical user interface that simplifies the annotation task and management.
year | journal | country | edition | language |
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2020-11-01 |