We propose a visualization method based on a topic model for discrete data such as documents. Unlike conventional visualization methods based on pairwise distances such as multi-d...
We investigate the novel problem of event recognition from news webpages. "Events" are basic text units containing news elements. We observe that a news article is always...
The latent topic model plays an important role in the unsupervised learning from a corpus, which provides a probabilistic interpretation of the corpus in terms of the latent topic...
Extraction based Multi-Document Summarization Algorithms consist of choosing sentences from the documents using some weighting mechanism and combining them into a summary. In this...