Computing semantic relatedness using Wikipedia-based explicit semantic analysis
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
ReadAlong: reading articles and comments together
Proceedings of the 20th international conference companion on World wide web
Narrowing the modeling gap: a cluster-ranking approach to coreference resolution
Journal of Artificial Intelligence Research
What users care about: a framework for social content alignment
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
Going beyond Corr-LDA for detecting specific comments on news & blogs
Proceedings of the 7th ACM international conference on Web search and data mining
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Comments constitute an important part of Web 2.0. In this paper, we consider comments on news articles. To simplify the task of relating the comment content to the article content the comments are about, we propose the idea of showing comments alongside article segments and explore automatic mapping of comments to article segments. This task is challenging because of the vocabulary mismatch between the articles and the comments. We present supervised and unsupervised techniques for aligning comments to segments the of article the comments are about. More specifically, we provide a novel formulation of supervised alignment problem using the framework of structured classification. Our experimental results show that structured classification model performs better than unsupervised matching and binary classification model.