NLP research at UBC

The Natural Language Processing (NLP) group at University of British Columbia conducts research in Computational Linguistics, Text Mining, Machine Learning, and Visual Text Analytics. The NLP@UBC group comprises of Two senior faculty members, two post-doctoral researchers, several graduate students, and undergraduate research assistants. We focus on the following research areas in particular (but not limited to):

• Discourse Parsing

  We have developed the top performer discourse parser. More details here.

• Mining and Summarizing Conversations (Emails, Meetings, Blogs, Chats)

  We have worked on several mining tasks, including topic segmentation and labeling, sentiment analysis, controversiality and extracting the conversational structure. We have also developed novel approaches to automatically generating extractive and abstractive summary of conversations.

• Understanding, Generating and Summarizing Evaluative Text

  In this direction, we have been working on generating evaluative arguments tailored to a model of the user preferences, as well as on generating multimedia extractive and abstractive summaries of large sets of evaluative documents (e.g., customer reviews)

• Visual Text Analytics for Conversations

  In this area, our aim is to tightly integrating interactive visualization with text mining and summarization techniques for information exploration and scalable decision support. We are focusing on creating visual text analytic systems for several domains including but not limited to meeting , emails, blogs, customer reviews, social media such as Facebook and twitter.

UBC Discourse Parser Demo

ConVis: A Visual Text Analytic System

Meeting browser

Interactive Visualization of Opinions