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2. List of concept- and mind-mapping software - Wikipedia

   en.wikipedia.org/wiki/List_of_concept-_and_mind...

   Concept mapping and mind mapping software is used to create diagrams of relationships between concepts, ideas, or other pieces of information. It has been suggested that the mind mapping technique can improve learning and study efficiency up to 15% over conventional note-taking. [1]

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4. Perplexity AI - Wikipedia

   en.wikipedia.org/wiki/Perplexity_AI

   Perplexity AI is a conversational search engine that uses large language models (LLMs) to answer queries using sources from the web and cites links within the text response. [ 3 ] [ 4 ] Its developer, Perplexity AI, Inc., is based in San Francisco, California .

5. Conceptual framework - Wikipedia

   en.wikipedia.org/wiki/Conceptual_framework

   The use of the term conceptual framework crosses both scale (large and small theories) [4] [5] and contexts (social science, [6] [7] marketing, [8] applied science, [9] art [10] etc.). The explicit definition of what a conceptual framework is and its application can therefore vary. Conceptual frameworks are beneficial as organizing devices in ...

6. Frame (artificial intelligence) - Wikipedia

   en.wikipedia.org/.../Frame_(artificial_intelligence)

   They were proposed by Marvin Minsky in his 1974 article "A Framework for Representing Knowledge". Frames are the primary data structure used in artificial intelligence frame languages; they are stored as ontologies of sets. Frames are also an extensive part of knowledge representation and reasoning schemes.

7. Metadesign - Wikipedia

   en.wikipedia.org/wiki/Metadesign

   Metadesign (or meta-design) is an emerging conceptual framework aimed at defining and creating social, economic and technical infrastructures in which new forms of collaborative design can take place. It consists of a series of practical design-related tools for achieving this.

8. Knowledge representation and reasoning - Wikipedia

   en.wikipedia.org/wiki/Knowledge_representation...

   Many of the early approaches to knowledge represention in Artificial Intelligence (AI) used graph representations and semantic networks, similar to knowledge graphs today. In such approaches, problem solving was a form of graph traversal [2] or path-finding, as in the A* search algorithm. Typical applications included robot plan-formation and ...

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