Comment centric news analysis for ranking

Authors


Abstract

Ranking documents to feed users' information need is a challenging task, due to the dynamic nature of users' interests with respect to a query, which changes from time to time. In this paper, I will propose the innovative method to extract a real-time language model estimation of the community interest given a query from, and use this model to rank retrieved documents. In this experiment, user comments tagged news (by using passage retrieval algorithm) collection is employed to represent community. The interest based ranking is differing from traditional relevance based ranking.

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