Knowledge Representation (KR) Engineering Task

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A Knowledge Representation (KR) Engineering Task is a knowledge creation task that is an engineering task (to created engineered knowledge).





  • (Kendal, 2007)
    • the building, maintaining and development of knowledge-based systems.


  • (Krauthammer & Nenadic, 2004) ⇒ Michael Krauthammer, and Goran Nenadic. (2004). “Term Identification in the Biomedical Literature.” In: Journal of Biomedical Informatics, 37(6). doi:10.1016/j.jbi.2004.08.004
    • Rule-based approaches generally attempt to recover terms by re-establishing associated term formation patterns that have been used to coin the terms in question.6 The main approach is to (typically manually) develop rules that describe common naming structures for certain term classes using either orthographic or lexical clues, or more complex morpho-syntactic features. Also, in many cases, dictionaries of typical term constituents (e.g. terminological heads, affixes, specific acronyms) are used to assist in term recognition. However, knowledge engineering approaches are known to be extremely time-consuming for development, and – since rules are typically very specific – their adjustment to other entities is usually difficult.


  • (Feigenbaum & McCorduck, 1983) ⇒ Edward A. Feigenbaum, and Pamela McCorduck. (1983). “The Fifth Generation (1st edition).” Addison-Wesley. ISBN:9780201115192
  • (Hayes-Roth et al., 1983) ⇒ Frederick Hayes-Roth, Donald Arthur Waterman, and Douglas B. Lenat, Eds. (1983). “Building Expert Systems.” Addison-Wesley. ISBN:0201106868
    • QUOTE: Over time, the knowledge engineering field will have an impact on all areas of human activity where knowledge provides the power for solving important problems. We can foresee two beneficial effects. The first and most obvious will be the development of knowledge systems that replicate and autonomously apply human expertise. For these systems, knowledge engineering will provide the technology for converting human knowledge into industrial power. The second benefit may be less obvious. As an inevitable side effect, knowledge engineering will catalyze a global effort to collect, codify, exchange and exploit applicable forms of human knowledge. In this way, knowledge engineering will accelerate the development, clarification, and expansion of human knowledge.