We present a term recognition approach to extract acronyms and their definitions from a large text collection. Parenthetical expressions appearing in a text collection are identif...
In this paper we propose a novel algorithm for opinion summarization that takes account of content and coherence, simultaneously. We consider a summary as a sequence of sentences ...
A novel maximal figure-of-merit (MFoM) learning approach to text categorization is proposed. Different from the conventional techniques, the proposed MFoM method attempts to integ...
Recommender systems improve access to relevant products and information by making personalized suggestions based on previous examples of a user's likes and dislikes. Most exi...
Dataset shift from the training data in a source domain to the data in a target domain poses a great challenge for many statistical learning methods. Most algorithms can be viewed ...