Towards an information extraction and knowledge formation framework based on Shannon entropy

Clicks: 407
ID: 49990
2017
Article Quality & Performance Metrics
Overall Quality Improving Quality
0.0 /100
Combines engagement data with AI-assessed academic quality
AI Quality Assessment
Not analyzed
Abstract
Information quantity subject is approached in this paperwork, considering the specific domain of nonconforming product management as information source. This work represents a case study. Raw data were gathered from a heavy industrial works company, information extraction and knowledge formation being considered herein. Involved method for information quantity estimation is based on Shannon entropy formula. Information and entropy spectrum are decomposed and analysed for extraction of specific information and knowledge-that formation. The result of the entropy analysis point out the information needed to be acquired by the involved organisation, this being presented as a specific knowledge type.
Reference Key
drago2017towardsmatec Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Dragoș, Iliescu;Marian, Gheorghe;
Journal matec web of conferences
Year 2017
DOI
DOI not found
URL
Keywords

Citations

No citations found. To add a citation, contact the admin at info@scimatic.org

No comments yet. Be the first to comment on this article.