Efficient Techniques for Improved Data Classification and POS Tagging by Monitoring Extraction, Pruning and Updating of Unknown Foreign Words

This paper presents an efficient text mining method focusing on extraction and updating of unknown words (unknown foreign words) to improve data classification and POS tags. Our proposed method used simple but efficient techniques, first it converts the data into structured form, using data preprocessing techniques. In this phase data passes through different stages, such as, cleaning, integration and selection of important data, and then it gets organized into databases for further analysis and processing. These database(s) consists of different kinds of dictionaries, our system heavily based on dictionaries. Our proposed methods for discovering and updating foreign unknown word, first discovers the foreign word using morphological analysis with the help of automatically and manually crated dictionaries, then suffix trimming and word segmentation, next our algorithm checks for its different written pattern using dictionaries according to its spelling and synonym word in native language (Korean) and also, updates the POS tags.