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Contents: Explanation: A Source of Guidance for Knowledge Representation.- (Re)Presentation Issues in Second Generation Expert Systems.- Some Aspects of Learning and Reorganization in an Analogical Representation.- A Knowledge-Intensive Learning System for Document Retrieval.- Constructing Expert Systems as Building Mental Models or Toward a Cognitive Ontology for Expert Systems.- Sloppy Modeling.- The Central Role of Explanations in DISCIPLE.- An Inference Engine for Representing Multiple Theories.- The Acquisition of Model-Knowledge for a Model-Driven Machine Learning Approach.- Using Attribute Dependencies for Rule Learning.- Learning Disjunctive Concepts.- The Use of Analogy in Incremental SBL.- Knowledge Base Refinement Using Apprenticeship Learning Techniques.- Creating High Level Knowledge Structures from Simple Elements.- Demand-Driven Concept Formation.
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| $99.99 | Digital |
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Michael Perik
reviewed Knowledge Representation and Organization in Machine Learning on November 29, 2015
Knowledge Representation and Organization in Machine Learning
It was an interesting read; like many history books, it feels to detailed at times, but this is just the way it is when reading academic books: They go the steps to make sure you understood why the argument is as it is (or at least think you did).
The topic was particularly interesting for me as my job is related to databases.
I wrote the most annotations for the section on cybernetics.
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Add Knowledge Representation and Organization in Machine Learning, Machine learning has become a rapidly growing field of Artificial Intelligence. Since the First International Workshop on Machine Learning in 1980, the number of scientists working in the field has been increasing steadily. This situation allows for speci, Knowledge Representation and Organization in Machine Learning to the inventory that you are selling on WonderClubX
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Add Knowledge Representation and Organization in Machine Learning, Machine learning has become a rapidly growing field of Artificial Intelligence. Since the First International Workshop on Machine Learning in 1980, the number of scientists working in the field has been increasing steadily. This situation allows for speci, Knowledge Representation and Organization in Machine Learning to your collection on WonderClub |