• Gebrehiwot Assefa Berhe

Tigrigna language is a Semitic language spoken by the Tigray people in Northern Ethiopia and Eritrea which has more than six million speakers worldwide. Even though the amount of the document increase, there are challenging tasks to identify the relevant documents related to a specific topic. So, a mechanism is required for finding, filtering and managing the rapid growth of online information. Hence, this study attempts to design a text categorization system. Here, clustering is used to find natural grouping of the unlabeled Tigrigna text documents. As a result, repeated bisection and direct k-means clustering algorithms are used to obtain documents of natural group of the Tigrigna data set. The repeated bisection clustering algorithm outperforms the direct k-means clustering algorithms.

categorization, text , clustering,algorithm, data set,k-means, repeated bisection

"Developing a Clustering Categorization Approach for Tigrigna Text", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 6, page no.865-872, June 2019, Available :http://www.jetir.org/papers/JETIR1907428.pdf

"Developing a Clustering Categorization Approach for Tigrigna Text", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 6, page no. pp865-872, June 2019, Available at : http://www.jetir.org/papers/JETIR1907428.pdf