Corpus ID: 6236390

Applying Textual Case-based Reasoning and Information Extraction in Lessons Learned Systems

@inproceedings{Ashley2000ApplyingTC,
  title={Applying Textual Case-based Reasoning and Information Extraction in Lessons Learned Systems},
  author={K. Ashley},
  year={2000}
}
  • K. Ashley
  • Published 2000
  • Computer Science
  • Textual Case-Based Reasoning and Information Extraction may assist in constructing Lessons Learned Systems where the lessons are texts. For a particular lesson domain, developers first should identify the kinds of information needed to compare lessons. Information Extraction techniques may then be applied in at least three ways to help extract such information automatically from lesson texts. 
    Intelligent lessons learned systems
    • 222
    • PDF
    Representing and Retrieving Knowledge Artifacts
    • 4
    • PDF
    Categorizing Intelligent Lessons Learned Systems
    • 12
    • PDF
    Categorizing Intelligent Lessons Learned Systems 1
    • 1
    • PDF

    References

    Publications referenced by this paper.
    SHOWING 1-10 OF 12 REFERENCES
    What You Saw Is What You Want: Using Cases to Seed Information Retrieval
    • 37
    Automatically Generating Extraction Patterns from Untagged Text
    • 711
    • PDF
    Text retrieval in the legal world
    • 86
    What Is Case-Based Reasoning?
    • 3,135
    Teaching case-based argumentation through a model and examples
    • 279
    Automatically Constructing a Dictionary for Information Extraction Tasks
    • 520
    • PDF
    Reasoning Symbolically About Partially Matched Cases
    • 32
    • PDF