受资源类型多样化、搜索复杂度的制约,现有的P2P文件共享系统中的搜索机制是基于文件名的关键字匹配,这种方法不能发现关键字与资源内容之间的深层关系,因此不能实现语义检索.针对这个问题,提出一种新的搜索方案,该方案建立在已有的搜索机制之上,利用用户的搜索行为和下载行为的规律自动发现关键字和资源间的深层关系,在底层的P2P网络上构建一个元数据空间以辅助搜索.该方案具有实现代价小、时间复杂度低、可进化和支持语义搜索的优点.在Maze系统上的实验表明,该方案具有较高的查询命中率和查询准确率.
Restricted by the diversity of resources and the complexity of search algorithms, current search mechanisms in peer-to-peer file sharing systems are based on file names and simple keyword matching. These mechanisms cannot recognize deeper relationships between keywords and resources; hence it cannot provide high search quality. This paper proposes a new search scheme, which is built on top of the current peer-to-peer network. It harnesses users' search behaviors and download behaviors to automatically discover the deeper relationships between keywords and resources, which is then used to improve the search quality. It has the advantages of low implementation cost, low complexity, self-evolving, and supports for semantic search. Simulations based on the Maze system show that this approach has high search hit rate and accuracy.