Term-weighting approaches in automatic text retrieval
Information Processing and Management: an International Journal
The anatomy of a large-scale hypertextual Web search engine
WWW7 Proceedings of the seventh international conference on World Wide Web 7
Authoritative sources in a hyperlinked environment
Proceedings of the ninth annual ACM-SIAM symposium on Discrete algorithms
A vector space model for automatic indexing
Communications of the ACM
Modern Information Retrieval
Introduction to Modern Information Retrieval
Introduction to Modern Information Retrieval
Introduction to Algorithms
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In modern information retrieval (IR) systems, scoring functions have been extensively adopted for sorting results. For a given document, the rank in sorted result lists with respect to hot searches can be considered as its influence. When a new document comes, can we use such IR systems to evaluate its influence before we insert it into the corpus? Such issue may not be solved very well by current IR systems with inverted indexes. In this paper, an influence measure based on documents’ global rank is proposed, and the inverted index structure has been extended by adding the position milestones for speeding up the ranking calculation. Moreover, a performance study using both real data and synthetic data verifies the effectiveness and the efficiency of our method.