In this paper, we propose a syllable-based method for tweet normalization to study the cognitive process of non-standard word creation in social media. Assuming that syllable play...
Annotations are increasingly created and shared online and connected with web resources such as databases of real-world entities. Recent collaborative efforts to provide interoper...
Sampo Pyysalo, Jorge Campos, Juan Miguel Cejuela, ...
The recently proposed neural network joint model (NNJM) (Devlin et al., 2014) augments the n-gram target language model with a heuristically chosen source context window, achievin...
Fandong Meng, Zhengdong Lu, Mingxuan Wang, Hang Li...
In order to effectively utilize multiple datasets with heterogeneous annotations, this paper proposes a coupled sequence labeling model that can directly learn and infer two heter...
Zhenghua Li, Jiayuan Chao, Min Zhang, Wenliang Che...
Natural language generation of coherent long texts like paragraphs or longer documents is a challenging problem for recurrent networks models. In this paper, we explore an importa...
We present AutoExtend, a system to learn embeddings for synsets and lexemes. It is flexible in that it can take any word embeddings as input and does not need an additional train...
We present and evaluate a method for automatically detecting sentence fragments in English texts written by non-native speakers. Our method combines syntactic parse tree patterns ...
It has been extensively observed that languages minimise the distance between two related words. Dependency length minimisation effects are explained as a means to reduce memory l...
In this paper, we introduce Long ShortTerm Memory (LSTM) recurrent network for twitter sentiment prediction. With the help of gates and constant error carousels in the memory bloc...