This paper presents Q-WordNet, a lexical resource consisting of WordNet senses automatically annotated by positive and negative polarity. Polarity classification amounts to decide...
Enterprises depend on their information workers finding valuable information to be productive. However, existing enterprise search and recommendation systems can exploit few studi...
This paper addresses the challenging problem of learning from multiple annotators whose labeling accuracy (reliability) differs and varies over time. We propose a framework based ...
Obtaining high-quality and up-to-date labeled data can be difficult in many real-world machine learning applications, especially for Internet classification tasks like review spam...
The analysis of texture is an important subroutine in application areas as diverse as biology, medicine, robotics, and forensic science. While the last three decades have seen ext...