343 citations · 894 across the 51 of their papers we have counts for
7 papers · 1 filter
Take and Took, Gaggle and Goose, Book and Read: Evaluating the Utility of Vector Differences for Lexical Relation Learning
Ekaterina Vylomova, Laura Rimell, Trevor Cohn +1
Recent work on word embeddings has shown that simple vector subtraction over pre-trained embeddings is surprisingly effective at capturing different lexical relations, despite lack…
Depth-Gated LSTM
Kaisheng Yao, Trevor Cohn, Katerina Vylomova +2
In this short note, we present an extension of long short-term memory (LSTM) neural networks to using a depth gate to connect memory cells of adjacent layers. Doing so introduces a…
Learning Structural Kernels for Natural Language Processing
Daniel Beck, Trevor Cohn, Christian Hardmeier +1
Structural kernels are a flexible learning paradigm that has been widely used in Natural Language Processing. However, the problem of model selection in kernel-based methods is usu…
Exploiting Text and Network Context for Geolocation of Social Media Users
Afshin Rahimi, Duy Vu, Trevor Cohn +1
Research on automatically geolocating social media users has conventionally been based on the text content of posts from a given user or the social network of the user, with very l…
Twitter User Geolocation Using a Unified Text and Network Prediction Model
Afshin Rahimi, Trevor Cohn, Timothy Baldwin
We propose a label propagation approach to geolocation prediction based on Modified Adsorption, with two enhancements:(1) the removal of "celebrity" nodes to increase location homo…
Classifying Tweet Level Judgements of Rumours in Social Media
Michal Lukasik, Trevor Cohn, Kalina Bontcheva
Social media is a rich source of rumours and corresponding community reactions. Rumours reflect different characteristics, some shared and some individual. We formulate the problem…
Structured Prediction of Sequences and Trees using Infinite Contexts
Ehsan Shareghi, Gholamreza Haffari, Trevor Cohn +1
Linguistic structures exhibit a rich array of global phenomena, however commonly used Markov models are unable to adequately describe these phenomena due to their strong locality a…