Experiences with selecting search engines using metasearch

被引:88
作者
Dreilinger, D [1 ]
Howe, AE [1 ]
机构
[1] COLORADO STATE UNIV,DEPT COMP SCI,FT COLLINS,CO 80523
关键词
algorithms; experimentation; information retrieval; machine learning; search engine; WWW;
D O I
10.1145/256163.256164
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Search engines are among the most useful and high-profile resources on the Internet. The problem of finding information on the Internet has been replaced with the problem of knowing where search engines are, what they are designed to retrieve, and how to use them. This article describes and evaluates SavvySearch, a metasearch engine designed to intelligently select and interface with multiple remote search engines. The primary metasearch issue examined is the importance of carefully selecting and ranking remote search engines for user queries; We studied the efficacy of SavvySearch's incrementally acquired metaindex approach to selecting search engines by analyzing the effect of time and experience on performance. We also compared the metaindex approach to the simpler categorical approach and showed how much experience is required to surpass the simple scheme.
引用
收藏
页码:195 / 222
页数:28
相关论文
共 12 条
[1]  
[Anonymous], 1994, MANAGING GIGABYTES C
[2]  
BOWMAN C, 1995, HARVEST SCALABLE CUS
[3]  
BOWMAN CM, 1994, COMMUN ACM, V37, P8
[4]  
DREILINGER DE, 1996, THESIS COLORADO STAT
[5]  
EICHMANN D, 1994, ELECT P 2 WORLD WID
[6]  
GAUCH S, 1996, J U COMPUT SCI, V2, P9
[7]  
GRAVANO L, 1994, P 3 INT C PAR DISTR
[8]  
Salton G., 1988, Automatic Text Processing: The Transformation, Analysis, and Retrieval of Information by Computer
[9]  
SELBERG E, 1995, P 4 INT WORLD WID WE
[10]  
SHELDON M, 1995, P 3 INT WORLD WID WE