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- W4256670603 abstract "Huge volume of relevant and irrelevant information is available from different sources for gaining knowledge about a system. If the required data is in a structured form, then the fact can be easily understood otherwise the process becomes laborious and results are vague after intense analysis. In this paper, we are proposing a framework for fetching knowledge from unstructured source of data. The algorithms proposed identifies the concepts and separates the concepts and relation words, enables to add new concepts and also modify the old concept word with new concept and locate the concept. This Concept-Relation Model enables the system to work according to the users’ connivance and deliveries accurate knowledge. This model does not manipulate or interpret the information provided but only represent and share the desired knowledge." @default.
- W4256670603 created "2022-05-12" @default.
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- W4256670603 date "2019-12-31" @default.
- W4256670603 modified "2023-09-27" @default.
- W4256670603 title "A Knowledge Representation Model using Concept-Relation Graph" @default.
- W4256670603 doi "https://doi.org/10.35940/ijeat.a1034.1291s319" @default.
- W4256670603 hasPublicationYear "2019" @default.
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