Compared with carefully edited prose, the language of social media is informal in the extreme. The application of NLP techniques in this context may require a better understanding...
Luchen Tan, Haotian Zhang, Charles L. A. Clarke, M...
Most previous work of text normalization on informal text made a strong assumption that the system has already known which tokens are non-standard words (NSW) and thus need normal...
Meaning of a word varies from one domain to another. Despite this important domain dependence in word semantics, existing word representation learning methods are bound to a singl...
Alcohol abuse may lead to unsociable behavior such as crime, drunk driving, or privacy leaks. We introduce automatic drunk-texting prediction as the task of identifying whether a ...
Aditya Joshi, Abhijit Mishra, Balamurali A. R, Pus...
We introduce C-PHRASE, a distributional semantic model that learns word representations by optimizing context prediction for phrases at all levels in a syntactic tree, from single...
Identifying the type of relationship between words provides a deeper insight into the history of a language and allows a better characterization of language relatedness. In this p...
This paper reports on and demonstrates META-SHARE/QT21, a prototype implementation of a data sharing and annotation service platform, which was based on the META-SHARE infrastruct...
Stelios Piperidis, Dimitrios Galanis, Juli Bakagia...
Stubs on Wikipedia often lack comprehensive information. The huge cost of editing Wikipedia and the presence of only a limited number of active contributors curb the consistent gr...
We propose a novel semantic parsing framework for question answering using a knowledge base. We define a query graph that resembles subgraphs of the knowledge base and can be dir...
Methods for name matching, an important component to support downstream tasks such as entity linking and entity clustering, have focused on alphabetic languages, primarily English...