互联网用户偏好本体实例的学习方法研究

Study on Instance Learning Method of Internet User Preference Ontology

互联网用户偏好本体可以全面、准确地描述出互联网用户的兴趣和多维偏好。针对偏好本体中主题类的实例对象数量众多、不断扩展变化、手工搜集工作量大这一问题,重点研究用户偏好本体中主题专业网站、品牌和体育赛事三类具有代表性的实例学习方法,以期实现互联网用户偏好本体的半自动构建,并设计实验验证这三类实例学习方法的有效性。

Internet user preference Ontology can fully and accurately describe the interest and multidimensional preference of Internet users. In order to effectively resolve the problem that a large number of instances which are expanding and varying are hard to collect manually, the learning method of three representative instances including the topic professional website, brand and sporting events is researched. This method can achieve semi - automatic construction of Internet user preference Ontology. The experiments are designed to verify the effectiveness of the method.