Web Document Clustering through Metafile Generation for Digraph Structure Using Document Index Graph

Clustering techniques are often used to cluster grouping text documents. Modeling and graph-based representation of the document clustering process can be done by using algorithms Document Index Graph (DIG). This study aims to implement the DIG algorithm for designing the structure digraphs used for graphical representation of web document clustering process. The data used is the REUTERS-21578 documents. Testing is done by determining the parameter values for the number of groups of documents to be processed and the determination of the frequency of occurrence of the word limit. Analysis performed on the stage of determining the limit frequency of occurrence of relevant words (inter-cluster) and the occurrence of the word that is not relevant (intra-cluster) on the document clustering process. Digraph structure that represents the best graph for document clustering process is achieved in inter-cluster frequency value 5 and the value of intra-cluster frequency 3 within 25 documents.