摘要
介绍了一个高效的元搜索引擎系统ISeeker,提出了一套全面的搜索引擎评价和选择算法,在对检索结果进行融合处理时尽可能选择最好的结果,而且在用户察看结果时进行在线学习和调整。
In this paper, an effective meta search engine ISeeker is introduced. ISeeker improves recall by sending search requests to multiple search engines. The results returned are fused to find out the best ones to show to the user in a proper manner. ISeeker tries to learn the user's interest rapidly while the user picks results to read and then adjust the remaining results to improve precision. Primary tests show that ISeeker is more efficient in some fields than search engines and meta search engines nowadays.
出处
《计算机工程》
CAS
CSCD
北大核心
2003年第10期41-42,52,共3页
Computer Engineering
基金
国家自然科学基金项目
国家"973"计划资助项目