This paper presents a novel opinion mining research problem, which is called Contrastive Opinion Modeling (COM). Given any query topic and a set of text collections from multiple ...
Topic-based text summaries promise to help average users quickly understand a text collection and derive insights. Recent research has shown that the Latent Dirichlet Allocation (...
Extractive multi-document summarization is the task of choosing sentences from a set of documents to compose a summary text in response to a user query. We propose a generative ap...
Most up-to-date well-behaved topic-based summarization systems are built upon the extractive framework. They score the sentences based on the associated features by manually assig...
This paper presents a model for summarizing multiple untranscribed spoken documents. Without assuming the availability of transcripts, the model modifies a recently proposed unsup...