面向食品安全领域的个性化知识搜索系统研究

发布时间：2018-08-27 12:20

【摘要】：大数据时代,从海量的数据中发现对用户有用的知识成为研究领域重要的问题.通过集成多个搜索引擎的查询结果,实现食品安全领域中搜索信息的集成和个性化自适应排序.本文设计基于元搜索技术、知识本体和自适应的排序学习技术,实现多个搜索引擎相关查询结果集成,在对用户点击的标注和知识本体的基础上,利用基于监督学习的排序技术,实现对食品安全领域信息的个性化自适应排序.系统实现了集成多个搜索引擎的食品安全相关知识的提取和相关结果的重新排序.本研究不仅实现了多个搜索引擎食品安全信息查询相关的结果集成,而且能够根据用户的偏好实现结果的自适应排序.
[Abstract]:In the era of big data, discovering useful knowledge from massive data has become an important issue in the field of research. By integrating the query results of multiple search engines, the integration of search information and personalized self-adaptive sorting in the field of food safety is realized. Based on meta-search technology, knowledge ontology and self-adaptive ranking learning technology, this paper designs the integration of query results related to multiple search engines, based on the annotation and knowledge ontology clicked by the user. The self-adaptive ordering of food safety information is realized by using the sorting technology based on supervised learning. The system realizes the extraction of food safety related knowledge and the reordering of the related results by integrating multiple search engines. This study not only realizes the integration of results related to food safety information query of multiple search engines, but also adaptively sorts the results according to users' preferences.
【作者单位】：南京农业大学信息科学技术学院;江苏省肉类生产与加工质量安全控制协同创新中心;
【基金】：国家自然科学基金(61502236) 中央高校基本科研业务费专项资金(KJQN201651,KYZ201752,KYZ201551) 国家科技支撑计划(2015BA1105000) 江苏省重点研发计划(BE2016803)
【分类号】：TP391.3

【相似文献】