Field-associated Terms itself have field Information. So, they determine field of document just like when human being perceives field. In case of Korean, we organized and experimented them by collecting approximately IS,999 document banks that are classified into 180 fields. We obtained high precision of extraction that 88,782 single field-associated terms are contracted into 8,405 ones thus recording compression rate as approximately 9$\%$ and recall as above 0.77 (average 0.85), precision as above 0.90 (average 0.94). By applying established field-associated terms to initial determination for document classification and comparing it with filed determination by human being, we got correct answers above approximately 90$\%$. We can use results of research as fundamental research for initial stage and apply it document retrieval between multilingual environment thus utilizing it as fundamental research for multilingual information retrieval.