• Medientyp: E-Artikel
  • Titel: Improvement on the Representation and Fusion Method of Fragmented Knowledge Structure
  • Beteiligte: Jia, Lili; Yang, Jinhua
  • Erschienen: IOP Publishing, 2020
  • Erschienen in: IOP Conference Series: Materials Science and Engineering
  • Sprache: Nicht zu entscheiden
  • DOI: 10.1088/1757-899x/750/1/012207
  • ISSN: 1757-8981; 1757-899X
  • Schlagwörter: General Medicine
  • Entstehung:
  • Anmerkungen:
  • Beschreibung: <jats:title>Abstract</jats:title> <jats:p>With the rapid development of Internet, cloud computing, Internet of things and other new technologies, information is growing exponentially, and human society has entered a new stage of fragmented knowledge. Fragmentation is flexible, random, and contains rich information, but fragmented information is fragmented, disordered, incomplete, large in size and fast in updating, so it is difficult to form effective knowledge. To resolve the problem of extracting and mining fragmented knowledge, firstly, this paper studies the fragmented knowledge map and he integration method of fragmented knowledge. secondly, we study the integration method of fragmented knowledge, from the aspects of incomplete and redundant fragmented information; Finally, we put forward several points of fragmented knowledge processing methods Key scientific issues and challenges.</jats:p>
  • Zugangsstatus: Freier Zugang