Social Text Normalization using Contextual Graph Random Walks

Adapting Sequence to Sequence models for Text Normalization in Social Media

Social media offer an abundant source of valuable raw data, however informal writing can quickly become a bottleneck for many natural language processing (NLP) tasks. Off-the-shelf tools are usually trained on formal tex…

A Graph-based Approach for Contextual Text Normalization

Improving Text Normalization by Optimizing Nearest Neighbor Matching

Text normalization is an essential task in the processing and analysis of social media that is dominated with informal writing. It aims to map informal words to their intended standard forms. Previously proposed text nor…

Deep Neural Models for Medical Concept Normalization in User-Generated Texts

In this work, we consider the medical concept normalization problem, i.e., the problem of mapping a health-related entity mention in a free-form text to a concept in a controlled vocabulary, usually to the standard thesa…

Semi-Parametric Contextual Bandits with Graph-Laplacian Regularization

Non-stationarity is ubiquitous in human behavior and addressing it in the contextual bandits is challenging. Several works have addressed the problem by investigating semi-parametric contextual bandits and warned that ig…