Alessandro Moschitti

Amazon, University of Trento
0000-0003-2216-8034
http://disi.unitn.it/moschitti/
Publications314
h-index49
Citations9,954
Highly Influential Citations917
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CoNLL-2012 Shared Task: Modeling Multilingual Unrestricted Coreference in OntoNotes
TLDR
OntoNotes provides a large-scale corpus of general anaphoric coreference not restricted to noun phrases or to a specified set of entity types and covering multiple languages. Expand
Towards Robust Linguistic Analysis using OntoNotes
TLDR
Large-scale linguistically annotated corpora have played a crucial role in advancing the state of the art of key natural language technologies such as syntactic, semantic and discourse analyzers, and they serve as training data. Expand
Learning to Rank Short Text Pairs with Convolutional Deep Neural Networks
TLDR
We present a convolutional neural network architecture for reranking short texts, where we learn the optimal representation of text pairs and a similarity function to relate them in a supervised way from the available training data. Expand
Efficient Convolution Kernels for Dependency and Constituent Syntactic Trees
TLDR
In this paper, we provide a study on the use of tree kernels to encode syntactic parsing information in natural language learning. Expand
Making Tree Kernels Practical for Natural Language Learning
TLDR
We show that tree kernels are very helpful in the processing of natural language as (a) we provide a simple algorithm to compute tree kernels in linear average running time and (b) our study on classification properties of diverse tree kernels show that kernel combinations always improve the traditional methods. Expand
Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP)
Twitter Sentiment Analysis with Deep Convolutional Neural Networks
TLDR
We propose a new model for initializing the parameter weights of the convolutional neural network, which is crucial to train an accurate model while avoiding the need to inject any additional features. Expand
A Study on Convolution Kernels for Shallow Statistic Parsing
TLDR
In this paper we have designed and experimented novel convolution kernels for automatic classification of predicate arguments. Expand
BART: A Modular Toolkit for Coreference Resolution
TLDR
We present BART, a highly modular toolkit for developing coreference applications. Expand
Exploiting Syntactic and Shallow Semantic Kernels for Question Answer Classification
TLDR
We study the impact of syntactic and shallow semantic information in automatic classification of questions and answers and answer re-ranking. Expand
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