干旱区生态环境知识资源中心

Mechanisms used for results merging are very important for distributed search systems. They are to select the most relevant documents retrieved by different servers and put them on the top of the list returned to the end user. There are several approaches to solve key problems of this task such as eliminating duplicates and ranking results combined. But it is still not clear how to achieve this. We use the clustering technique to divide retrieved results into several groups and a metric on the base of the vector space model to arrange items inside each group. Preliminary tests were conducted using the OASIS system and several collections of real Internet data. They showed relatively superior results when compared to the neural network clustering and LSI calculation. Proposed mechanisms can be applied to metasearch systems and to distributed search systems as well because such mechanisms do not require any special information except standard de facto data received from servers.