Generating summaries that meet the information needs of a user relies on (1) several forms of question decomposition; (2) different summarization approaches; and (3) textual inference for combining the summarization strategies. This novel framework for summarization has the advantage of producing highly responsive summaries, as indicated by the evaluation results. 2007 Elsevier Ltd. All rights ...

© Document summarization using Wikipedia Krishnan Ramanathan, Yogesh Sankarasubramaniam, Nidhi Mathur, Ajay Gupta HP Laboratories HPL-2009-39 Single Document Summarization, Wikipedia, ROUGE Although most of the developing world is likely to first access the Internet through mobile phones, mobile devices are constrained by screen space, bandwidth and limited attention span. Single document summa...

We describe our participation in the Multilingual Summarization Evaluation 2005. We describe the Columbia summarizers that were used in our submission and discuss the evaluation, drawing conclusions about the performance of our summarizers, discussing the state of multilingual summarization in general and also listing issues that need consideration for future evaluations.

We present Power Mean Pyramid Scores (PMP), an evaluation metric that extends the Pyramid evaluation scheme for summarization by combining Sentence Content Units (SCU) scores using Power Mean. The Pyramid method generates a summarization score by linearly combining component SCU scores. We find that by combining SCU scores using Power Mean, we can optimize a single parameter, α, leading to sign...

How do graph clustering techniques compare with respect to their summarization power? How well can they summarize a million-node graph with a few representative structures? Graph clustering or community detection algorithms can summarize a graph in terms of coherent and tightly connected clusters. In this paper, we compare and contrast different techniques: METIS, Louvain, spectral clustering, ...

This paper describes an approach to building a trainable multi-document summarization system, using a simple training process based on support vector machines. The summarization system is trained and tested using the DUC 2005 data set. The evaluation results based on ROUGE scores are presented and methods for improving the performance of the summarization system are identified.

This paper surveys current text and speech summarization evaluation approaches. It discusses advantages and disadvantages of these, with the goal of identifying summarization techniques most suitable to speech summarization. Precision/recall schemes, as well as summary accuracy measures which incorporate weightings based on multiple human decisions, are suggested as particularly suitable in eva...

This paper surveys current text and speech summarization evaluation approaches. It discusses advantages and disadvantages of these, with the goal of identifying summarization techniques most suitable to speech summarization. Precision/recall schemes, as well as summary accuracy measures which incorporate weightings based on multiple human decisions, are suggested as particularly suitable in eva...