[1]许建豪.采用向量空间模型的个性化信息检索方法[J].华侨大学学报(自然科学版),2016,37(2):175-178.[doi:10.11830/ISSN.1000-5013.2016.02.0175]
　XU Jianhao.Research on Personalized Information Retrieval Method Using Vector Space Model[J].Journal of Huaqiao University(Natural Science),2016,37(2):175-178.[doi:10.11830/ISSN.1000-5013.2016.02.0175]
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采用向量空间模型的个性化信息检索方法()
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《华侨大学学报（自然科学版）》[ISSN:1000-5013/CN:35-1079/N]

卷:
第37卷
期数:
2016年第2期
页码:
175-178
栏目:
出版日期:
2016-03-20

文章信息/Info

Title:
Research on Personalized Information Retrieval Method Using Vector Space Model
文章编号:
1000-5013(2016)02-0175-04
作者:
许建豪
南宁职业技术学院 信息工程学院, 广西 南宁 530008
Author(s):
XU Jianhao
School of Information Engineering, Nanning College for Vocational Technology, Nanning 530008, China
关键词:
信息检索;  向量空间模型;  个性化需求;  语料库
Keywords:
information retrieval;  vector space model;  personalized needs;  corpus
分类号:
TP181
DOI:
10.11830/ISSN.1000-5013.2016.02.0175
文献标志码:
A
摘要:
为了提升检索结果与用户个性化需求的符合程度,依托向量空间模型提出一种新的检索方法.将用户查询关键词和语料库内的文本信息都映射为向量,从而把检索过程转化为向量相似性的比对.在比对过程中,通过关键词权重突出用户个性化需求,通过余弦相似度判断符合程度.实验结果表明:文中方法的检索结果与用户需求的符合程度明显提高.
Abstract:
In order to improve matching degree between the retrieval results and of user’s personalized needs, a new method based on vector space model is proposed in this paper. Maps the user query keywords and the text information in the database to the many vectors, and then transforms the retrieval process to the comparison of the vector similarity. In the process, the user’s personalized needs are highlighted by the keyword weight, and the matching degree is determined by the cosine similarity. Experimental results show that the retrieval results of this method are significantly improved with the user’s requirements.

参考文献/References:

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备注/Memo

备注/Memo:
收稿日期: 2015-12-25
通信作者: 许建豪(1977-),男,副教授,主要从事网络技术及信息检索的研究.E-mail:jianhaoxu@yeah.net.
基金项目: 广西高校科研基金资助项目(YB2014495)
更新日期/Last Update: 2016-03-20