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Yajuan Duan

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2 papers

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IJCAI Conference 2013 Conference Paper

Answer Extraction from Passage Graph for Question Answering

Hong Sun
Nan Duan
Yajuan Duan
Ming Zhou

In question answering, answer extraction aims to pin-point the exact answer from passages. However, most previous methods perform such extraction on each passage separately, without considering clues provided in other passages. This paper presents a novel approach to extract answers by fully leveraging connections among different passages. Specially, extraction is performed on a Passage Graph which is built by adding links upon multiple passages. Different passages are connected by linking words with the same stem. We use the factor graph as our model for answer extraction. Experimental results on multiple QA data sets demonstrate that our method significantly improves the performance of answer extraction.

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AAAI Conference 2013 Conference Paper

The Automated Acquisition of Suggestions from Tweets

Li Dong
Furu Wei
Yajuan Duan
Xiaohua Liu
Ming Zhou
Ke Xu

This paper targets at automatically detecting and classifying user’s suggestions from tweets. The short and informal nature of tweets, along with the imbalanced characteristics of suggestion tweets, makes the task extremely challenging. To this end, we develop a classification framework on Factorization Machines, which is effective and efficient especially in classification tasks with feature sparsity settings. Moreover, we tackle the imbalance problem by introducing cost-sensitive learning techniques in Factorization Machines. Extensively experimental studies on a manually annotated real-life data set show that the proposed approach significantly improves the baseline approach, and yields the precision of 71. 06% and recall of 67. 86%. We also investigate the reason why Factorization Machines perform better. Finally, we introduce the first manually annotated dataset for suggestion classification.

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