Volume 34 Issue 06
Jun.  2008
Turn off MathJax
Article Contents
Chen Jiangfeng, Yu Jianjun. Topic model based structural Web services discovery[J]. Journal of Beijing University of Aeronautics and Astronautics, 2008, 34(06): 734-738. (in Chinese)
Citation: Chen Jiangfeng, Yu Jianjun. Topic model based structural Web services discovery[J]. Journal of Beijing University of Aeronautics and Astronautics, 2008, 34(06): 734-738. (in Chinese)

Topic model based structural Web services discovery

  • Received Date: 04 Mar 2007
  • Publish Date: 30 Jun 2008
  • A structural Web services discovery approach based on a topic model was proposed. Each Web service would be modeled as a structural textual document using probabilistic model generated by latent dirichlet allocation (LDA). Every document could be seen as a multinomial random mixture of topics, and each topic had multinomial distribution over keywords, and thus a Web service retrieval based on the topic model was put forward. At the same time, the similar correlations in functionally structural Web services could be modeled as a directed acyclic graph (DAG) and be measured by using a gap-weighted n-spectrum kernel. Finally the experiment results show that several metrics for the classification and selection of services, such as success rate and executes efficiency, were improved via using our approach.

     

  • loading
  • [1] Deerwester S, Dumais S, Furnas G.Indexing by latent semantic analysis[J]. Journal of the American Society for Information Science, 1990, 41:391-407 [2] Hofman T. Probabilistic latent semantic indexing Gey Fredric,Hearst Marti, Tong Richard. Proceedings of the 22nd Annual International ACM SIGIR Conference. New York:ACM,1999:50-57 [3] Blei D M, Ng A Y, Jordan M. Latent dirichlet allocation[J]. Journal of Machine Learning Research,2003,3(1):993-1022 [4] Li W, McCallum A. Pachinko allocation:DAG-structured mixture models of topic correlations Cohen William,Moore Andrew. Proceedings of the 23rd International Conference on Machine Learning. New York:ACM,2006:577-584 [5] Blei D M, Lafferty J D. Dynamic topic models Cohen William, Moore Andrew. Proceedings of the 23rd International Conference on Machine Learning. New York:ACM,2006:113-120 [6] Shawe-Taylor J,Cristianini N. Kernel methods for pattern analysis[M]. United Kingdom:Cambridge University Press,2004:344-372
  • 加载中

Catalog

    通讯作者: 陈斌, bchen63@163.com
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

    1. 本站搜索
    2. 百度学术搜索
    3. 万方数据库搜索
    4. CNKI搜索

    Article Metrics

    Article views(3068) PDF downloads(1030) Cited by()
    Proportional views
    Related

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return