[1]陈燕红[],刘风华[]. 一种改进的潜在语义检索模型研究[J].计算机技术与发展,2014,24(09):120-124.
　 Study on Improved Latent Semantic Retrieval Model[J].,2014,24(09):120-124.
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 一种改进的潜在语义检索模型研究()
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《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
24
期数:
2014年09期
页码:
120-124
栏目:
智能、算法、系统工程
出版日期:
2014-09-10

文章信息/Info

Title:
 Study on Improved Latent Semantic Retrieval Model
文章编号:
1673-629X（2014）09-0120-05
作者:
 陈燕红[1]; 刘风华[2]
 1.新疆农业大学 计算机与信息工程学院；2.新疆工程学院 计算机工程系,新疆
Author(s):
 CHEN Yan-hong[1]，LIU Feng-hua[2]
关键词:
 ; 农业信息; 垂直搜索引擎; 潜在语义检索; 面向农业的潜在语义检索模型
Keywords:
 ; gricultural information; vertical search engine; latent semantic indexing; ALSI
分类号:
TP31
文献标志码:
A
摘要:
 针对传统潜在语义检索模型计算成本大、检索速度慢、不利于应用在大规模农业信息检索领域的缺陷,文中提出一种针对农业主题的改进潜在语义检索模型( ALSI)。该模型先利用全文检索生成农业信息全文倒排索引库,然后利用农业高频词库和潜在语义分析生成的语义索引库,进行语义检索。通过多组实验分析确定了该模型所采用的词条权重计算方法和语义空间维数。最后,通过实验分析对比了改进后的潜在语义检索模型( ALSI)与传统潜在语义检索模型( LSI)的检索效果。结果表明,ALSI的检索效果明显好于LSI,适合应用于较大规模农业信息检索。
Abstract:
 For some defects that the traditional latent semantic retrieval model is big cost,slow retrieval speed,and not conducive to the field in large-scale agriculture information retrieval,present an improved Agriculture Latent Semantic Indexing ( ALSI) model. The mod-el uses full-text search to generate full-text inverted index of agricultural information,and then utilizes agricultural high-frequency vo-cabulary and latent semantic to analyze generated semantic indexing databases,completing semantic retrieval. By analyzing multiple sets of experiments,determine calculation methods of term weight and semantic space dimension. Finally,analyze and juxtapose search results of ALSI and the traditional LSI through experiment,the results show that retrieval results of ALSI is significantly better than LSI,and AL-SI is suitable for the large-scale agricultural information retrieval.

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更新日期/Last Update: 2015-04-01