tailieunhanh - Báo cáo khoa học: "Comparative News Summarization Using Linear Programming"

Comparative News Summarization aims to highlight the commonalities and differences between two comparable news topics. In this study, we propose a novel approach to generating comparative news summaries. We formulate the task as an optimization problem of selecting proper sentences to maximize the comparativeness within the summary and the representativeness to both news topics. We consider semantic-related cross-topic concept pairs as comparative evidences, and consider topic-related concepts as representative evidences | Comparative News Summarization Using Linear Programming Xiaojiang Huang Xiaojun Wan Jianguo Xiao Institute of Computer Science and Technology Peking University Beijing 100871 China Key Laboratory of Computational Linguistic Peking University MOE China huangxiaojiang wanxiaojun xiaojianguo @ Abstract Comparative News Summarization aims to highlight the commonalities and differences between two comparable news topics. In this study we propose a novel approach to generating comparative news summaries. We formulate the task as an optimization problem of selecting proper sentences to maximize the comparativeness within the summary and the representativeness to both news topics. We consider semantic-related cross-topic concept pairs as comparative evidences and consider topic-related concepts as representative evidences. The optimization problem is addressed by using a linear programming model. The experimental results demonstrate the effectiveness of our proposed model. 1 Introduction Comparative News Summarization aims to highlight the commonalities and differences between two comparable news topics. It can help users to analyze trends draw lessons from the past and gain insights about similar situations. For example by comparing the information about mining accidents in Chile and China we can discover what leads to the different endings and how to avoid those tragedies. Comparative text mining has drawn much attention in recent years. The proposed works differ in the domain of corpus the source of comparison and the representing form of results. So far most researches focus on comparing review opinions of products Liu et al. 2005 Jindal and Liu 2006a Corresponding author 648 Jindal and Liu 2006b Lerman and McDonald 2009 Kim and Zhai 2009 . A reason is that the aspects in reviews are easy to be extracted and the comparisons have simple patterns . positive vs. negative. A few other works have also tried to compare facts and views in news article Zhai .

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