标题：Text Classification Method Based on Machine Learning and Domain Knowledge Ontology
作者：Gao, Zhiyong; Qiao, Shuhan; Liang, Yongquan
作者机构：[Gao, Zhiyong; Liang, Yongquan] Shandong Univ Sci & Technol, Coll Informat Sci & Engn, Qingdao, Peoples R China.; [Qiao, Shuhan] Shandong Agr Univ, 更多
会议名称：International Conference on Modeling, Simulation and Optimization Technologies and Applications (MSOTA)
会议日期：DEC 18-19, 2016
来源：PROCEEDINGS OF 2016 INTERNATIONAL CONFERENCE ON MODELING, SIMULATION AND OPTIMIZATION TECHNOLOGIES AND APPLICATIONS (MSOTA2016)
关键词：machine learning; ontology; text classification
摘要：The use of machine learning method is discussed herein to produce a corpus by domain knowledge ontology and conduct text classification according to the ontology of professional knowledge domain. Nowadays, a large number of literature materials have been accumulated in each professional field, and it is still in rapid growth. This constitutes a great challenge for researchers in various fields. To be specific, not only the workload in literature retrieval and reading is constantly increased, but also the work efficiency of the study is affected. In this paper, ontology is taken as the text feature extractor for storage, processing, classification and retrieval through ontology development tools Protege, Jena and natural language processing tool NLTK, so as to facilitate the researcher for literature retrieval and reading. The advantage of this text classification method lies in that category structure is no longer a single tree structure, but instead, different categories may intersect and new category may be grouped by themselves.