State of the Art Method

In this paper we present a supervised method for back-of-the-book index construction. We introduce a novel set of features that goes be- yond the typical frequency-based analysis, in- cluding features …...

Scripts representing common sense knowledge about stereotyped sequences of events have been shown to be a valu- able resource for NLP applications. We present a hierarchical Bayesian model for unsupervised …...

We present a new context-aware method for lexical simplification that uses two free lan- guage resources and real web frequencies. We compare it with the state-of-the-art method for lexical simplification …...

This paper proposes a method for intra- sentential subject zero anaphora resolution in Japanese. Our proposed method utilizes a Multi-column Convolutional Neural Network (MCNN) for predicting zero anaphoric rela- tions. …...

Event extraction from texts aims to de- tect structured information such as what has happened, to whom, where and when. Event extraction and visualization are typ- ically considered as two …...

AbstractRecognising dialogue acts (DA) is important for many natural language processing tasks such as dialogue generation and intention recognition. In this paper, we propose a dual-attention hierarchical recurrent neural network …...

AbstractConcept map-based multi-document summarization has recently been proposed as a variant of the traditional summarization task with graph-structured summaries. As shown by previous work, the grouping of coreferent concept mentions …...

AbstractHealthcare is becoming a more and more important research topic recently. With the growing data in the healthcare domain, it offers a great opportunity for deep learning to improve the …...

AbstractContinual Learning for Named Entity Recognition (CL-NER) aims to learn a growing number of entity types over time from a stream of data. However, simply learning Other-Class in the same …...