Clustering as a Tool for Categorization of Unstructured Data - Gogo, Ngor; EO, Bennett (International Journal of Computer Sciences and Engineering, 2019)
The volume of information untapped are locked up in huge volume of text documents (unstructured data) that could aid the economy, government, individuals and corporate organisation to improve on the state of life and develop better working system cannot be overemphasized, therefore the need to extract this information and give a structure that will facilitate its proper storage and access when required becomes so important. The target of this research is to explore Clustering as a Tool for Categorizing Unstructured Data (Text document). The K-Prototype Algorithm was applied for the purpose of clustering these unstructured data to give structure to it. There are two major phases involved in this: first is the pre-processing phase (Tokenization, Stemming, and Stop Word Removal) and secondly the clustering phase. The system built performed better as shown from the result, that it can be use to categorise text documents for proper and easy storage and accessibility.