Abstract:

Ranking the documents in a list has been extensively used in a lot of search engine systems. In these systems, vector space based ranking models are adopted. Actually, the ranking score of a given document is invisible to search engine users, and the rank position can be regarded as a measure of the influence of a given document. However, for a document outside corpus, how can we measure the influence of it? The question cannot be answered by using ordinary search engines. Social influence is introduced on a real microblogging system. Moreover, a large number of milestones are added into inverted indices for the sake of estimating the influence scores. Therefore, above questions can be well answered. The experiments on real data sets verify the effectiveness and efficiency.

Key words: information retrieval;inverted index;TFIDF;milestone