全部 标题 作者
关键词 摘要

OALib Journal期刊
ISSN: 2333-9721
费用:99美元

查看量下载量

相关文章

更多...
-  2015 

面向维基百科服务计算领域的演化知识树 Evolution Knowledge Tree for Services Computing Domain in Wikipedia

Keywords: 文档-主题-热点,Gibbs抽样,演化知识树,维基百科热点

Full-Text   Cite this paper   Add to My Lib

Abstract:

针对已有知识树知识热点不突出、知识分类不准确以及结构不断演化等问题,本文面向维基百科的中文数据库"服务计算"领域密集型数据,提出了扩展的中文分词算法,抽取、分类出多种主题知识及其结构化信息,结合服务计算领域文档提出基于LDA改进的DKHM(文档-主题-热点)模型,使用Gibbs抽样算法对数据集采样,并消除原词条歧义分类,以建立演化知识树.实验结果表明:基于DKHM的聚类准确度高于一般的贝叶斯聚类,通过聚类发现的热点与真实热点的匹配度达60%以上,从而验证了演化知识树比维基百科原有知识树结构更合理,热点趋势效果更明显

References

[1]  金芝,何克清,王青.软件需求工程:部分研究工作进展[J].中国计算机学会通讯,2007,3(11):25-34.Jin Z,He K Q,Wang Q.Software requirements engineering:progress of research work[J].Communication of China Computer Federation,2007,3(11):25-34(Ch).
[2]  史天艺,李明禄.基于维基百科的自动词义消歧方法[J].计算机工程,2009,35(18):62-64.Shi T Y,Li M L.Automatic world sense disambiguation method based on wikipedia[J].Computer Engineering,2009,35(18):62-64(Ch).
[3]  涂新辉,张红春,周琨峰,等.中文维基百科的结构化信息抽取及词语相关度计算方法[J].中文信息学报,2012,26(3):109-115.Xu X H,Zhang H C,Zhou K F,et al.Extracting structured information from chinese Wikipedia and measuring relatedness between words[J].Journal of Chinese Information Processing,2012,26(3):109-115(Ch).
[4]  孙萍,蒋昌俊.利用服务聚类优化面向过程模型的语义Web服务发现[J].计算机学报,2008,31(8):1340-1353.Sun P,Jiang C J.Using service clustering to facilitate process-oriented semantic Web service discovery[J].Chinese Journal of Computers,2008,31(8):1340-1353(Ch).
[5]  Walsh B.Markov chain Monte Carlo and Gibbs sampling[DB/OL].[2014-08-06].http://cos.name/2013/01/lda-math-math-mcmc-and-gidds-sampling/
[6]  Segaran T.Programming Collective Intelligence:Building Smart Web2.0 Applications[M].New York:O’Reilly Media,2007.
[7]  欧振猛,余顺争.中文分词算法在搜索引擎应用中的研究[J].计算机工程与应用,2000,36(8):80-82.Ou Z M,Xu S Z.Research of Chinese Word Automatic Segmentation used in Search Engine[J].Computer Engineering and Applications,2000,36(8):80-82(Ch).
[8]  徐燕,王斌,李锦涛,等.知识增益:文本分类中一种新的特征选择方法[J].中文信息学报,2008,22(1):44-50.Xu Y,Wang B,Li J T,et al.Knowledge gain:A new method of feature selection in text categorization[J].Journal of Chinese Information Processing,2008,22(1):44-50(Ch).
[9]  Platzer C,Rosenberg F,Dustdar S.Web service clustering using multidimensional angles as proximity measures[J].ACM Transactions on Internet Technology,2009,9(3):1-26.
[10]  Yu Q,Rege M.On service community learning:A coclustering approach[C]//Proc of IEEE Int Conf on Web Services.Piscataway:IEEE,2010:283-290.
[11]  Liu J X,He K Q,Wang J,et al.A clustering method for Web service discovery[C]//Proc of IEEE Int Conf on Services Computing.Piscataway:IEEE,2011:729-730.
[12]  陈江锋,于建军.基于主题模型的结构化Web服务发现机制[J].北京航空航天大学学报,2008,34(6):734-738.Chen J F,Yu J J.Topic model based structural Web services discovery[J].Journal of Beijing University of Aeronautics and Astronautics,2008,34(6):734-738(Ch).

Full-Text

Contact Us

service@oalib.com

QQ:3279437679

WhatsApp +8615387084133