Design of an Intelligent Agent for Job Assignments based on Document Classification

• Main Authors: Jui His, 傅瑞曦
• Other Authors: Singling Lee
• Format: Others
• Language: en_US
• Published: 2006
• Online Access: http://ndltd.ncl.edu.tw/handle/51823450023071639777

碩士 === 國立中正大學 === 資訊工程所 === 95 === Some systems are built to manage those information, like information classification which differentiates between the useful and the useless or classifies information into categories. Currently, we found that some jobs are described into words, so we can assign jobs according to the words. This concept could be used in dispatching official documents. If we use techniques of document classification, dispatching official documents (job assignments) would be done automatically or semi-artificially. Automatic job-assignment could not only save human effort but maintain the knowledge and keep the precision of the assignment. Considering performance and efficiency of the system, we use the statistical method of document classification to calculate the possibility of each category by term frequencies as term weights and continuous terms for increasing weights. In our simulation, the whole classification procedure costs less than 20 ms even if there are 40000 documents in the domain knowledge, and the precision of our method could reach 70%.