This paper describes an emotion-based approach to acquire sentiment similarity of word pairs with respect to their senses. Sentiment similarity indicates the similarity between tw...
Mitra Mohtarami, Hadi Amiri, Man Lan, Thanh Phu Tr...
As the popularity of the social media increases, as evidenced in Twitter, Facebook and China’s Renren, spamming activities also picked up in numbers and variety. On social netwo...
Yin Zhu, Xiao Wang, ErHeng Zhong, Nathan Nan Liu, ...
To solve the sparsity problem in collaborative filtering, researchers have introduced transfer learning as a viable approach to make use of auxiliary data. Most previous transfer...
Widespread accounts of the harmful effects of invasive species have stimulated both practical and theoretical studies on how the spread of these destructive agents can be containe...
Hashing, which tries to learn similarity-preserving binary codes for data representation, has been widely used for efficient nearest neighbor search in massive databases due to i...
Given a monochrome image and some manually labeled pixels, the colorization problem is a computer-assisted process of adding color to the monochrome image. This paper proposes a n...
We tackle the problem of defining a well-founded semantics (WFS) for Datalog rules with existentially quantified variables in their heads and negations in their bodies. In partic...
Most Twitter search systems generally treat a tweet as a plain text when modeling relevance. However, a series of conventions allows users to tweet in structural ways using combin...
Zhunchen Luo, Miles Osborne, Sasa Petrovic, Ting W...
We explore the problem of assigning heterogeneous tasks to workers with different, unknown skill sets in crowdsourcing markets such as Amazon Mechanical Turk. We first formalize ...
In AI research, mechanism design is typically used to allocate tasks and resources to agents holding private information about their values for possible allocations. In this conte...
Lachlan Thomas Dufton, Victor Naroditskiy, Maria P...