In this paper, we propose a novel approach to automatic generation of aspect-oriented summaries from multiple documents. We first develop an event-aspect LDA model to cluster sen...
We consider ranking and clustering problems related to the aggregation of inconsistent information. Ailon, Charikar, and Newman [1] proposed randomized constant factor approximatio...
Previous methods usually conduct the keyphrase extraction task for single documents separately without interactions for each document, under the assumption that the documents are ...
In this paper we present a fast and accurate procedure called clustered low rank matrix approximation for massive graphs. The procedure involves a fast clustering of the graph and...
Abstract. In this paper we propose the clustering of top-ranking sentences (TRS) for effective information access. Top-ranking sentences are selected by a query-biased sentence ex...