WEB DOCUMENT RETRIEVAL USING MANIFOLD LEARNING AND ACO ALGORITHM

摘要：

To efficiently deal with high dimensionality and precision problems in document retrieval, a novel document retrieval algorithm based on manifold learning and ant colony optimization(ACO) algorithm is proposed. The high-dimensional document data are first projected into lowerdimensional feature space with neighborhood preserving embedding (NPE) algorithm, the ACO algorithm is then applied to retrieve relevant documents in the reduced lower-dimensionality document feature space. Extensive experiments on real-world data set demonstrate the effectiveness of the proposed algorithm.

关键词： Document retrieval manifold learning neighborhood preserving embedding(NPE) ant colony optimization(ACO)

作者: Wang Ziqiang Sun Xia

作者单位: School of Information Science and Engineering,Henan University of Technology, Zhengzhou

会议类型: 国际会议

会议名称: 2009 2nd IEEE International Conference on Broadband Network & Multimedia Technology(2009年宽带网络与多媒体国际会议 IEEE IC-BNMT2009)

会议地点: 北京

会议语种:英文

页码: 152-155

在线出版日期: 2009-10-18（万方平台首次上网日期，不代表论文的发表时间）