基于语义Web的多功能情报信息自适应检索技术
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摘要
为了解决传统依据关键字、概念和属性值等检索技术没有考虑不同主体中情报信息间的语义关系,无法提供令用户满意的情报检索结果问题;通过语义Web方法研究了多功能情报信息自适应检索技术。设计基于语义Web的多功能情报信息自适应检索模型。检索模型包括人机交互层、知识处理层以及知识存储层。在知识存储层建立本体语义模型。在知识处理层,从检索的多功能情报信息关键词中推断和其语义有关的概念,依据概念有关词汇对原始查询进行扩展,对语义相似度进行计算。在人机交互层,将用户反馈情况看作判断检索结果优劣的衡量因素;依据相似关键词获取相似结果集,按照反馈因子完成对所有相似结果的排序,把排序结果发送给用户,实现多功能情报信息自适应检索。结果表明,所提方法能够同时保证召回率与精度;排序误差率低;检索结果和用户查询结果最相符,检索结果准确,可令用户满意。可见所提方法检索性能强。
In order to solve the problem that traditional retrieval techniques based on keywords,concepts and attribute values do not consider the semantic relationship between information in different subjects and can not provide satisfactory information retrieval results to users,a multi-functional information adaptive retrieval technique is studied by semantic Web method. A multi-functional information adaptive retrieval model based on semantic Web is designed. The retrieval model includes human-computer interaction layer,knowledge processing layer and knowledge storage layer. An ontology semantic model is established in the knowledge storage layer. In the knowledge processing layer,the semantic related concepts are inferred from the multi-functional information keywords retrieved,and the original query is expanded according to the related concepts,and the semantic similarity is calculated. In the human-computer interaction layer,user feedback is regarded as a measure factor to judge the quality of retrieval results. Similar result sets are obtained according to similar keywords,and all similar results are sorted according to feedback factors. The sorting results are sent to users to realize multi-functional information adaptive retrieval. The results show that the proposed method can guarantee the recall rate and precision at the same time,the sorting error rate is low,the retrieval results are most consistent with the user's query results,and the retrieval results are accurate and satisfying to users. It is obvious that the retrieval performance of the proposed method is strong.
In order to solve the problem that traditional retrieval techniques based on keywords,concepts and attribute values do not consider the semantic relationship between information in different subjects and can not provide satisfactory information retrieval results to users,a multi-functional information adaptive retrieval technique is studied by semantic Web method. A multi-functional information adaptive retrieval model based on semantic Web is designed. The retrieval model includes human-computer interaction layer,knowledge processing layer and knowledge storage layer. An ontology semantic model is established in the knowledge storage layer. In the knowledge processing layer,the semantic related concepts are inferred from the multi-functional information keywords retrieved,and the original query is expanded according to the related concepts,and the semantic similarity is calculated. In the human-computer interaction layer,user feedback is regarded as a measure factor to judge the quality of retrieval results. Similar result sets are obtained according to similar keywords,and all similar results are sorted according to feedback factors. The sorting results are sent to users to realize multi-functional information adaptive retrieval. The results show that the proposed method can guarantee the recall rate and precision at the same time,the sorting error rate is low,the retrieval results are most consistent with the user's query results,and the retrieval results are accurate and satisfying to users. It is obvious that the retrieval performance of the proposed method is strong.
引文
1谢文亮,王石榴.基于语义Web的科技期刊网络信息检索及其应用[J].科技管理研究,2015,35(2):196-200Xie Wenliang,Wang Shiliu. Semantic web-based network information retrieval for scientific periodical journal and its application[J]. Science and Technology Management Research,2015,35(2):196-200
2 苏依拉,吉亚图,窦葆媛.基于蒙古语课程领域语义Web的推理与检索方法的研究[J].计算机工程与科学,2016,38(2):376-385Su Yila,Ji Yatu,Dou Baoyuan. A semantic web-based reasoning and retrieval method in mongolian curriculum[J]. Computer Engineering and Science,2016,38(2):376-385
3 Thangaraj M,Sujatha G. An architectural design for effective information retrieval in semantic web[J]. Expert Systems with Applications,2014,41(18):8225-8233
4 姬鹏飞,李远刚,卢盛祺,等.基于语义Web的旅游路线个性化定制系统[J].计算机工程,2016,42(10):308-317Ji Pengfei,Li Yuangang,Lu Shengqi,et al. Personalized customization system of travel route based on semantic Web[J]. Computer Engineering,2016,42(10):308-317
5 伍振兴,曾令伟,汪文彬.基于概念格特征分区的多源信息检索优化[J].科技通报,2015,31(8):174-176Wu Zhenxing,Zeng Lingwei,Wang Wenbin. Optimization of multisource information retrieval based on concept lattice feature partition[J]. Bulletin of Science and Technology,2015,31(8):174-176
6 冯勇,刘瑶,徐红艳.一种基于标签用户模型的个性化信息检索方法[J].小型微型计算机系统,2014,35(9):2004-2008Feng Yong,Liu Yao,Xu Hongyan. Personalized information retrieval method based on tag user model[J]. Journal of Chinese Computer Systems,2014,35(9):2004-2008
7 郭猛,胡秀香,邵国金.混合语义相似度计算优化模糊查询的智能信息检索算法[J].科学技术与工程,2014,14(23):97-102Guo Meng,Hu Xiuxiang,Shao Guojin. Intelligent information retrieval algorithm based on fuzzy query optimized by hybrid semantic similarity computing[J]. Science Technology and Engineering,2014,14(23):97-102
8 唐郑熠,韦立,李均涛,等.语义Web中本体概念的语义匹配分离方法[J].计算机工程与设计,2014,35(11):4054-4060Tang Zhengyi,Wei Li,Li Juntao,et al. Separation method of semantic matching for ontology concept in semantic Web[J]. Computer Engineering and Design,2014,35(11):4054-4060
9 Qin F,Gao S,Yang X,et al. An ontology-based semantic retrieval approach for heterogeneous 3D CAD models[J]. Advanced Engineering Informatics,2016,30(4):751-768
10 欧石燕,唐振贵,苏翡斐.面向信息检索的术语服务构建与应用研究[J].中国图书馆学报,2016,42(2):32-51Ou Shiyan,Tang Zhengui,Su Feifei. Construction and usage of terminology services for information retrieval[J]. Journal of Library Science in China,2016,42(2):32-51
11 崔道江,陈琳,李勇.智能检索引擎中的网络数据挖掘技术优化研究[J].计算机测量与控制,2017,25(6):189-191Cui Daojiang,Chen Lin,Li Yong. Research on optimization of network data mining technology in intelligent retrieval engine[J]. Computer Measurement&Control,2017,25(6):189-191
12 吴丹,李一喆.老年人网络健康信息检索行为实验研究[J].图书情报工作,2014,58(12):102-108Wu Dan,Li Yizhe. An experiment study on older adults'online health information seeking behavior[J]. Library and Information Service,2014,58(12):102-108
13 Zapater J J S,EscriváD M L,García F R S,et al. Semantic web service discovery system for road traffic information services[J]. Expert Systems with Applications,2015,42(8):3833-3842
14 王元卓,贾岩涛,刘大伟,等.基于开放网络知识的信息检索与数据挖掘[J].计算机研究与发展,2015,52(2):456-474Wang Yuanzhuo,Jia Yantao,Liu Dawei,et al. Open web knowledge aided information search and data mining[J]. Journal of Computer Research and Development,2015,52(2):456-474
15 刘哲.大型数据库需求信息实时查询优化仿真[J].计算机仿真,2017,34(1):427-430Liu Zhe. Real time query optimization and simulation of large database demand information[J]. Computer Simulation,2017,34(1):427-430
16 周静,张书亮,张小波.顾及地理实体的地名信息检索方法研究[J].地球信息科学学报,2015,17(11):1362-1369Zhou Jing,Zhang Shuliang,Zhang Xiaobo. A place name information retrieval method considering geographic entity[J]. Journal of Geo-information Science,2015,17(11):1362-1369
17 姜赢,张婧,朱玲萱.基于本体的家谱知识图谱模型及检索系统[J].电子设计工程,2017,25(12):161-165Jiang Ying,Zhang Jing,Zhu Lingxuan. Ontology based knowledge graph model of genealogical record and retrieval system[J]. Electronic Design Engineering,2017,25(12):161-165
2 苏依拉,吉亚图,窦葆媛.基于蒙古语课程领域语义Web的推理与检索方法的研究[J].计算机工程与科学,2016,38(2):376-385Su Yila,Ji Yatu,Dou Baoyuan. A semantic web-based reasoning and retrieval method in mongolian curriculum[J]. Computer Engineering and Science,2016,38(2):376-385
3 Thangaraj M,Sujatha G. An architectural design for effective information retrieval in semantic web[J]. Expert Systems with Applications,2014,41(18):8225-8233
4 姬鹏飞,李远刚,卢盛祺,等.基于语义Web的旅游路线个性化定制系统[J].计算机工程,2016,42(10):308-317Ji Pengfei,Li Yuangang,Lu Shengqi,et al. Personalized customization system of travel route based on semantic Web[J]. Computer Engineering,2016,42(10):308-317
5 伍振兴,曾令伟,汪文彬.基于概念格特征分区的多源信息检索优化[J].科技通报,2015,31(8):174-176Wu Zhenxing,Zeng Lingwei,Wang Wenbin. Optimization of multisource information retrieval based on concept lattice feature partition[J]. Bulletin of Science and Technology,2015,31(8):174-176
6 冯勇,刘瑶,徐红艳.一种基于标签用户模型的个性化信息检索方法[J].小型微型计算机系统,2014,35(9):2004-2008Feng Yong,Liu Yao,Xu Hongyan. Personalized information retrieval method based on tag user model[J]. Journal of Chinese Computer Systems,2014,35(9):2004-2008
7 郭猛,胡秀香,邵国金.混合语义相似度计算优化模糊查询的智能信息检索算法[J].科学技术与工程,2014,14(23):97-102Guo Meng,Hu Xiuxiang,Shao Guojin. Intelligent information retrieval algorithm based on fuzzy query optimized by hybrid semantic similarity computing[J]. Science Technology and Engineering,2014,14(23):97-102
8 唐郑熠,韦立,李均涛,等.语义Web中本体概念的语义匹配分离方法[J].计算机工程与设计,2014,35(11):4054-4060Tang Zhengyi,Wei Li,Li Juntao,et al. Separation method of semantic matching for ontology concept in semantic Web[J]. Computer Engineering and Design,2014,35(11):4054-4060
9 Qin F,Gao S,Yang X,et al. An ontology-based semantic retrieval approach for heterogeneous 3D CAD models[J]. Advanced Engineering Informatics,2016,30(4):751-768
10 欧石燕,唐振贵,苏翡斐.面向信息检索的术语服务构建与应用研究[J].中国图书馆学报,2016,42(2):32-51Ou Shiyan,Tang Zhengui,Su Feifei. Construction and usage of terminology services for information retrieval[J]. Journal of Library Science in China,2016,42(2):32-51
11 崔道江,陈琳,李勇.智能检索引擎中的网络数据挖掘技术优化研究[J].计算机测量与控制,2017,25(6):189-191Cui Daojiang,Chen Lin,Li Yong. Research on optimization of network data mining technology in intelligent retrieval engine[J]. Computer Measurement&Control,2017,25(6):189-191
12 吴丹,李一喆.老年人网络健康信息检索行为实验研究[J].图书情报工作,2014,58(12):102-108Wu Dan,Li Yizhe. An experiment study on older adults'online health information seeking behavior[J]. Library and Information Service,2014,58(12):102-108
13 Zapater J J S,EscriváD M L,García F R S,et al. Semantic web service discovery system for road traffic information services[J]. Expert Systems with Applications,2015,42(8):3833-3842
14 王元卓,贾岩涛,刘大伟,等.基于开放网络知识的信息检索与数据挖掘[J].计算机研究与发展,2015,52(2):456-474Wang Yuanzhuo,Jia Yantao,Liu Dawei,et al. Open web knowledge aided information search and data mining[J]. Journal of Computer Research and Development,2015,52(2):456-474
15 刘哲.大型数据库需求信息实时查询优化仿真[J].计算机仿真,2017,34(1):427-430Liu Zhe. Real time query optimization and simulation of large database demand information[J]. Computer Simulation,2017,34(1):427-430
16 周静,张书亮,张小波.顾及地理实体的地名信息检索方法研究[J].地球信息科学学报,2015,17(11):1362-1369Zhou Jing,Zhang Shuliang,Zhang Xiaobo. A place name information retrieval method considering geographic entity[J]. Journal of Geo-information Science,2015,17(11):1362-1369
17 姜赢,张婧,朱玲萱.基于本体的家谱知识图谱模型及检索系统[J].电子设计工程,2017,25(12):161-165Jiang Ying,Zhang Jing,Zhu Lingxuan. Ontology based knowledge graph model of genealogical record and retrieval system[J]. Electronic Design Engineering,2017,25(12):161-165