Survey: Understand the challenges of MachineLearning Experts using Named EntityRecognition Tools
Journal:
arXiv
Published Date:
Jan 27, 2025
Abstract
This paper presents a survey based on Kasunic's survey research methodology
to identify the criteria used by Machine Learning (ML) experts to evaluate
Named Entity Recognition (NER) tools and frameworks. Comparison and selection
of NER tools and frameworks is a critical step in leveraging NER for
Information Retrieval to support the development of Clinical Practice
Guidelines. In addition, this study examines the main challenges faced by ML
experts when choosing suitable NER tools and frameworks. Using Nunamaker's
methodology, the article begins with an introduction to the topic,
contextualizes the research, reviews the state-of-the-art in science and
technology, and identifies challenges for an expert survey on NER tools and
frameworks. This is followed by a description of the survey's design and
implementation. The paper concludes with an evaluation of the survey results
and the insights gained, ending with a summary and conclusions.
