关键词: 关键词:Web对象;对象级搜索;链接分析

Abstract:

Abstract: This paper proposes a novel domainindependent objectlevel ranking model. Given a set of objects and their

relationships, this model provides a ranked list of objects based on their relevance to multiple query objects supplied by the

user. We present a multi-plane object relationship graph to describe the space of objectlevel search, an algorithm for

evaluating the popularity values of objects based on the object relationship graph, and an algorithm for evaluating the

relevance ratings of objects based on the query object as well as merging multiple query objects. The effectiveness of this

model is experimentally verified on the ACM data set. This model provides a better paper recommendation performance than

PaperRank. This model also outperforms PaperRank on merging the relevance ratings of multiple query objects into a single

vector.

Key words: Key words: Web objects; object-level search; link analysis