http://idl-bnc.idrc.ca:80/dspace/handle/10625/49272 2013-05-18T11:14:27Z http://idl-bnc.idrc.ca:80/dspace/handle/10625/49750 Title: Summarizing Similar Questions for Chinese Community Question Answering Portals Authors: Tang, Yang; Li, Fangtao; Huang, Minlie; Zhu, Xiaoyan Abstract: As online community question answering (cQA) portals like Yahoo! Answers1 and Baidu Zhidao2 have attracted over hundreds of millions of questions, how to utilize these questions and accordant answers becomes increasingly important for cQA websites. Prior approaches focus on using information retrieval techniques to provide a ranked list of questions based on their similarities to the query. Due to the high variance of question quality and answer quality, users have to spend lots of time on finding the truly best answers from retrieved results. In this paper, we develop an answer retrieval and summarization system which directly provides an accurate and comprehensive answer summary instead of a list of similar questions to user’s query. To fully explore the information of relations between queries and questions, between questions and answers, and between answers and sentences, we propose a new probabilistic scoring model to distinguish high-quality answers from low-quality answers. By fully exploiting these relations, we summarize answers using a maximum coverage model. Experiment results on the data extracted from Chinese cQA websites demonstrate the efficacy of our proposed method. 2010-01-01T00:00:00Z http://idl-bnc.idrc.ca:80/dspace/handle/10625/49748 Title: Multi-document Summarization by Information Distance Authors: Long, C; Huang, M L; Zhu, X Y; Li, M Abstract: Fast changing knowledge on the Internet can be acquired more efficiently with the help of automatic document summarization and updating techniques. This paper described a novel approach for multi-document update summarization. The best summary is defined to be the one which has the minimum information distance to the entire document set. The best update summary has the minimum conditional information distance to a document cluster given that a prior document cluster has already been read. Experiments on the DUC 2007 dataset and the TAC 2008 dataset have proved that our method closely correlates with the human summaries and outperforms other programs such as LexRank in many categories under the ROUGE evaluation criterion. 2009-01-01T00:00:00Z http://idl-bnc.idrc.ca:80/dspace/handle/10625/49746 Title: A New Approach for Multi-Document Update Summarization Authors: Long, Chong; Huang, Min-Lie; Zhu, Xiao-Yan; Li, Ming Abstract: Fast changing knowledge on the Internet can be acquired more efficiently with the help of automatic document summarization and updating techniques. This paper describes a novel approach for multi-document update summarization. The best summary is defined to be the one which has the minimum information distance to the entire document set. The best update summary has the minimum conditional information distance to a document cluster given that a prior document cluster has already been read. Experiments on the DUC/TAC 2007 to 2009 datasets (http://duc.nist.gov/, http://www.nist.gov/tac/) have proved that our method closely correlates with the human summaries and outperforms other programs such as LexRank in many categories under the ROUGE evaluation criterion. 2010-01-01T00:00:00Z http://idl-bnc.idrc.ca:80/dspace/handle/10625/49063 Title: Specialized Review Selection for Feature Rating Estimation Authors: Long, Chong; Zhang, Lei; Huang, Minlie; Zhu, Xiaoyan; Li, Ming Abstract: On participatory Websites, users provide opinions about products, with both overall ratings and textual reviews. In this paper, we propose an approach to accurately estimate feature ratings of the products. This approach selects user reviews that extensively discuss specific features of the products (called specialized reviews), using information distance of reviews on the features. Experiments on real data show that overall ratings of the specialized reviews can be used to represent their feature ratings. The average of these overall ratings can be used by recommender systems to provide feature specific recommendations that better help users make purchasing decisions. Description: 2009 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Workshops 2009-09-01T00:00:00Z http://idl-bnc.idrc.ca:80/dspace/handle/10625/49062 Title: Answering Opinion Questions with Random Walks on Graphs Authors: Li, Fangtao; Tang, Yang; Huang, Minlie; Zhu, Xiaoyan Abstract: Opinion Question Answering (Opinion QA), which aims to find the authors’ sentimental opinions on a specific target, is more challenging than traditional fact-based question answering problems. To extract the opinion oriented answers, we need to consider both topic relevance and opinion sentiment issues. Current solutions to this problem are mostly ad-hoc combinations of question topic information and opinion information. In this paper, we propose an Opinion PageRank model and an Opinion HITS model to fully explore the information from different relations among questions and answers, answers and answers, and topics and opinions. By fully exploiting these relations, the experiment results show that our proposed algorithms outperform several state of the art baselines on benchmark data set. A gain of over 10% in F scores is achieved as compared to many other systems. Description: Proceedings of the 47th Annual Meeting of the ACL and the 4th IJCNLP of the AFNLP 2009-08-01T00:00:00Z