Semantic lexical matching is a prominent subtask within text understanding applications. Yet, it is rarely evaluated in a direct manner. This paper proposes a definition for lexic...
In this paper, we present ParaEval, an automatic evaluation framework that uses paraphrases to improve the quality of machine translation evaluations. Previous work has focused on...
This paper presents a corrective model for speech recognition of inflected languages. The model, based on a discriminative framework, incorporates word ngrams features as well as ...
This paper explores the use of two graph algorithms for unsupervised induction and tagging of nominal word senses based on corpora. Our main contribution is the optimization of th...
Co-occurrence analysis has been used to determine related words or terms in many NLP-related applications such as query expansion in Information Retrieval (IR). However, related w...
Reordering is currently one of the most important problems in statistical machine translation systems. This paper presents a novel strategy for dealing with it: statistical machin...
Random Indexing is a vector space technique that provides an efficient and scalable approximation to distributional similarity problems. We present experiments showing Random Inde...
NLP systems for tasks such as question answering and information extraction typically rely on statistical parsers. But the efficacy of such parsers can be surprisingly low, partic...
Alexander Yates, Stefan Schoenmackers, Oren Etzion...
The automatic recognition of the rhetorical function of citations in scientific text has many applications, from improvement of impact factor calculations to text summarisation an...
We present two discriminative methods for name transliteration. The methods correspond to local and global modeling approaches in modeling structured output spaces. Both methods d...