38 citations · 134 across the 12 of their papers we have counts for
10 papers · 1 filter
Dual-FOFE-net Neural Models for Entity Linking with PageRank
Feng Wei, Uyen Trang Nguyen, Hui Jiang
This paper presents a simple and computationally efficient approach for entity linking (EL), compared with recurrent neural networks (RNNs) or convolutional neural networks (CNNs),…
Effective Context and Fragment Feature Usage for Named Entity Recognition
Nargiza Nosirova, Mingbin Xu, Hui Jiang
In this paper, we explore a new approach to named entity recognition (NER) with the goal of learning from context and fragment features more effectively, contributing to the improv…
A Multi-task Learning Approach for Named Entity Recognition using Local Detection
Nargiza Nosirova, Mingbin Xu, Hui Jiang
Named entity recognition (NER) systems that perform well require task-related and manually annotated datasets. However, they are expensive to develop, and are thus limited in size.…
A General FOFE-net Framework for Simple and Effective Question Answering over Knowledge Bases
Dekun Wu, Nana Nosirova, Hui Jiang +1
Question answering over knowledge base (KB-QA) has recently become a popular research topic in NLP. One popular way to solve the KB-QA problem is to make use of a pipeline of sever…
Fixed-Size Ordinally Forgetting Encoding Based Word Sense Disambiguation
Xi Zhu, Mingbin Xu, Hui Jiang
In this paper, we present our method of using fixed-size ordinally forgetting encoding (FOFE) to solve the word sense disambiguation (WSD) problem. FOFE enables us to encode variab…
The Lower The Simpler: Simplifying Hierarchical Recurrent Models
Chao Wang, Hui Jiang
To improve the training efficiency of hierarchical recurrent models without compromising their performance, we propose a strategy named as `the lower the simpler', which is to simp…