The Cubic Regression Model for Merging Results from Multiple Text Databases

摘要：

In a distributed information retrieval system, how to merge results from different text databases is an important issue, since it affects the effectiveness of the result considerably. In many cases, the underlining systems only provide a ranked list of documents for any information need. In this paper, we investigate the relation between rank and relevance in resultant document lists, and find that the cubic model is a good option for this. Extensive experimentation is conducted to evaluate the performance of the cubic model for results merging. The experimental results demonstrate that the cubic model is better than the logistic model, which was suggested by a previous research.

关键词： distributed information retrieval results merging text databases cubic regression model

作者: Shengli Wu Yaxin Bi Jun Liu

作者单位: School of Computing and Mathematics University of Ulster Newtownabbey, UK

会议类型: 国际会议

会议名称: Fifth International Conference on Semantics,Knowledge and Grid(第五届语义、知识与网格国际会议 SKG 2009)

会议地点: 珠海

会议语种:英文

页码: 3-10

在线出版日期: 2009-10-12（万方平台首次上网日期，不代表论文的发表时间）