Knowledge Processing Task
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A Knowledge Processing Task is a human-level intelligence task whose task input is knowledge.
- AKA: Knowledge Work, Knowledge-Intensive Task.
- Context:
- It can that involves significant application of Process Rules.
- It can be performed by a Knowledge Processing System (such as a knowledge worker or an automated knowledge processing system).
- It can (typically) involve a Complex Reading Task.
- It can (typically) involve a Writing Task.
- ...
- Example(s):
- Software Programming.
- Medical Diagnosis.
- Legal Contract Analysis.
- Deductive Inferencing;
- Knowledge Management (e.g. Fensel 2001, Mullholland et al. 2000; Staab & Schnurr, 2000; Sure et al., 2000, Abecker et al. 1997);
- Electronic Commerce (e.g. RosettaNet and Ontology.org)
- NLP Tasks (Nirenburg et al., 2004, Maedche et al., 2001, Agirre et al., 1996, Beale et al., 1995);
- simplify understanding and change, because the Domain Assumptions are explicitly stated.
- enable Reuse, because the Domain Knowledge is separated from the Operational Knowledge.
- to support Existential Queries, such as: "What concepts, relationships, and constraints exist?"
- …
- Counter-Example(s):
- an Unskilled Task.
- See: Knowledge, Skilled Task.
References
2011
- http://en.wikipedia.org/wiki/Knowledge_worker#Knowledge_worker_roles
- Knowledge workers bring benefits to organizations in a variety of important ways. These include:
- analyzing data to establish relationships
- assessing input in order to evaluate complex or conflicting priorities
- identifying and understanding trends
- making connections
- understanding cause and effect.
- ability to brainstorm, thinking broadly (divergent thinking)
- ability to drill down, creating more focus (convergent thinking)
- producing a new capability
- creating or modifying a strategy
- These knowledge worker contributions are in contrast with activities that they would typically not be asked to perform, including:
- transaction processing
- routine tasks
- simple prioritization of work
- Knowledge workers bring benefits to organizations in a variety of important ways. These include:
2003
- (Maedche et al., 2003a) ⇒ Alexander Maedche, Boris Motik, Ljiljana Stojanovic, Rudi Studer, and Raphael Volz. (2003). “Ontologies for Enterprise Knowledge Management.” In: IEEE Intelligent Systems, 18(2). doi:10.1109/MIS.2003.1193654
- QUOTE: Ontologies are a key technology for enabling semantics-driven knowledge processing, and it is widely accepted that the next generation of knowledge management system will rely on conceptual models in the form of ontologies.