Improvements for Determining the Number of Clusters in k-Means for Innovation Databases in SMEs.
Amelec ViloriaOmar Bonerge Pineda LezamaPublished in: ANT/EDI40 (2019)
Keyphrases
- databases
- k means
- knowledge management
- technological innovation
- relational databases
- database
- case study
- data integration
- knowledge discovery
- database systems
- data model
- machine learning
- business processes
- cluster analysis
- small and medium enterprises
- fuzzy k means
- clustering approaches
- data warehouse
- self organizing maps
- clustering method
- data management
- learning algorithm
- real world
- real time