@article{ETD,
      recid = {368},
      author = {Hollingshead, Kristy},
      title = {Formalizing the use and characteristics of constraints in  pipeline systems},
      publisher = {Oregon Health and Science University},
      school = {Ph.D.},
      address = {2010},
      number = {ETD},
      abstract = {Pipeline systems, widely used in natural language  processing and other fields, process data through  sequential stages to improve efficiency, manage search  complexity, and reuse components. Despite their prevalence,  little systematic work has examined how these systems  function or how best to improve them. This dissertation  defines a formal framework based on shared properties of  pipelines across domains such as parsing, speech  recognition, machine translation, and image classification.  It introduces quantitative metrics describing constraint  characteristics and demonstrates that commonly used  measures of constraint quality are poor predictors of  performance. The findings show that systematically  modifying constraint properties can meaningfully affect  pipeline performance, offering broadly applicable guidance  for analyzing and improving pipeline systems.},
      url = {http://digitalcollections.ohsu.edu/record/368},
      doi = {https://doi.org/10.6083/M49K4860},
}